Available Benchmarks¶
BEIR¶
Zero-shot retrieval quality across a heterogeneous set of IR tasks and domains, providing a common framework for comparing NLP-based retrieval models.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| TRECCOVID | Retrieval | text | eng |
| NFCorpus | Retrieval | text | eng |
| NQ | Retrieval | text | eng |
| HotpotQA | Retrieval | text | eng |
| FiQA2018 | Retrieval | text | eng |
| ArguAna | Retrieval | text | eng |
| Touche2020 | Retrieval | text | eng |
| CQADupstackRetrieval | Retrieval | text | eng |
| QuoraRetrieval | Retrieval | text | eng |
| DBPedia | Retrieval | text | eng |
| SCIDOCS | Retrieval | text | eng |
| FEVER | Retrieval | text | eng |
| ClimateFEVER | Retrieval | text | eng |
| SciFact | Retrieval | text | eng |
| MSMARCO | Retrieval | text | eng |
Citation
@inproceedings{thakur2021beir,
archiveprefix = {arXiv},
author = {Nandan Thakur and Nils Reimers and Andreas R{\"u}ckl{\'e} and Abhishek Srivastava and Iryna Gurevych},
booktitle = {Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2)},
eprint = {2104.08663},
title = {{BEIR}: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models},
url = {https://openreview.net/forum?id=wCu6T5xFjeJ},
year = {2021},
}
BEIR-NL¶
Zero-shot retrieval quality in Dutch across the BEIR task suite, created through automated translation of the original English benchmark.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| ArguAna-NL | Retrieval | text | nld |
| CQADupstack-NL | Retrieval | text | nld |
| FEVER-NL | Retrieval | text | nld |
| NQ-NL | Retrieval | text | nld |
| Touche2020-NL | Retrieval | text | nld |
| FiQA2018-NL | Retrieval | text | nld |
| Quora-NL | Retrieval | text | nld |
| HotpotQA-NL | Retrieval | text | nld |
| SCIDOCS-NL | Retrieval | text | nld |
| ClimateFEVER-NL | Retrieval | text | nld |
| mMARCO-NL | Retrieval | text | nld |
| SciFact-NL | Retrieval | text | nld |
| DBPedia-NL | Retrieval | text | nld |
| NFCorpus-NL | Retrieval | text | nld |
| TRECCOVID-NL | Retrieval | text | nld |
Citation
@inproceedings{banar2024beirnlzeroshotinformationretrieval,
address = {Abu Dhabi, UAE},
archiveprefix = {arXiv},
author = {Lotfi, Ehsan and Banar, Nikolay and Daelemans, Walter},
booktitle = {Proceedings of the 18th Workshop on Building and Using Comparable Corpora ({BUCC})},
editor = {Sharoff, Serge and Terryn, Ayla Rigouts and Zweigenbaum, Pierre and Rapp, Reinhard},
eprint = {2412.08329},
month = {jan},
pages = {36--45},
publisher = {Association for Computational Linguistics},
title = {{BEIR}-{NL}: Zero-shot Information Retrieval Benchmark for the {D}utch Language},
url = {https://aclanthology.org/2025.bucc-1.5/},
year = {2025},
}
BEIR-PL¶
Zero-shot retrieval quality in Polish across the BEIR task suite, covering biomedical, financial, legal, and general knowledge domains.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| MSMARCO-PL | Retrieval | text | pol |
| TRECCOVID-PL | Retrieval | text | pol |
| NFCorpus-PL | Retrieval | text | pol |
| NQ-PL | Retrieval | text | pol |
| HotpotQA-PL | Retrieval | text | pol |
| FiQA-PL | Retrieval | text | pol |
| ArguAna-PL | Retrieval | text | pol |
| Touche2020-PL | Retrieval | text | pol |
| CQADupstackRetrieval-PL | Retrieval | text | pol |
| Quora-PL | Retrieval | text | pol |
| DBPedia-PL | Retrieval | text | pol |
| SCIDOCS-PL | Retrieval | text | pol |
| SciFact-PL | Retrieval | text | pol |
Citation
@misc{wojtasik2024beirpl,
archiveprefix = {arXiv},
author = {Konrad Wojtasik and Vadim Shishkin and Kacper Wołowiec and Arkadiusz Janz and Maciej Piasecki},
eprint = {2305.19840},
primaryclass = {cs.IR},
title = {BEIR-PL: Zero Shot Information Retrieval Benchmark for the Polish Language},
url = {https://arxiv.org/abs/2305.19840},
year = {2024},
}
BRIGHT¶
Reasoning-intensive retrieval quality across real-world queries spanning diverse domains including economics, psychology, mathematics, and coding, drawn from naturally occurring and carefully curated human data.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| BrightRetrieval | Retrieval | text | eng |
Citation
@inproceedings{su2024bright,
archiveprefix = {arXiv},
author = {Hongjin SU and Howard Yen and Mengzhou Xia and Weijia Shi and Niklas Muennighoff and Han-yu Wang and Liu Haisu and Quan Shi and Zachary S Siegel and Michael Tang and Ruoxi Sun and Jinsung Yoon and Sercan O Arik and Danqi Chen and Tao Yu},
booktitle = {The Thirteenth International Conference on Learning Representations},
eprint = {2407.12883},
title = {{BRIGHT}: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval},
url = {https://openreview.net/forum?id=ykuc5q381b},
year = {2025},
}
BRIGHT (long)¶
Reasoning-intensive retrieval quality across real-world queries spanning diverse domains, filtered to longer documents to stress-test models on extended contexts.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| BrightLongRetrieval | Retrieval | text | eng |
Citation
@inproceedings{su2024bright,
archiveprefix = {arXiv},
author = {Hongjin SU and Howard Yen and Mengzhou Xia and Weijia Shi and Niklas Muennighoff and Han-yu Wang and Liu Haisu and Quan Shi and Zachary S Siegel and Michael Tang and Ruoxi Sun and Jinsung Yoon and Sercan O Arik and Danqi Chen and Tao Yu},
booktitle = {The Thirteenth International Conference on Learning Representations},
eprint = {2407.12883},
title = {{BRIGHT}: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval},
url = {https://openreview.net/forum?id=ykuc5q381b},
year = {2025},
}
BRIGHT(v1.1)¶
Reasoning-intensive retrieval quality across real-world queries spanning diverse domains including economics, psychology, mathematics, and coding. v1.1 restructures tasks into separate datasets and adds per-task prompts.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| BrightBiologyRetrieval | Retrieval | text | eng |
| BrightEarthScienceRetrieval | Retrieval | text | eng |
| BrightEconomicsRetrieval | Retrieval | text | eng |
| BrightPsychologyRetrieval | Retrieval | text | eng |
| BrightRoboticsRetrieval | Retrieval | text | eng |
| BrightStackoverflowRetrieval | Retrieval | text | eng |
| BrightSustainableLivingRetrieval | Retrieval | text | eng |
| BrightPonyRetrieval | Retrieval | text | eng |
| BrightLeetcodeRetrieval | Retrieval | text | eng |
| BrightAopsRetrieval | Retrieval | text | eng |
| BrightTheoremQATheoremsRetrieval | Retrieval | text | eng |
| BrightTheoremQAQuestionsRetrieval | Retrieval | text | eng |
| BrightBiologyLongRetrieval | Retrieval | text | eng |
| BrightEarthScienceLongRetrieval | Retrieval | text | eng |
| BrightEconomicsLongRetrieval | Retrieval | text | eng |
| BrightPsychologyLongRetrieval | Retrieval | text | eng |
| BrightRoboticsLongRetrieval | Retrieval | text | eng |
| BrightStackoverflowLongRetrieval | Retrieval | text | eng |
| BrightSustainableLivingLongRetrieval | Retrieval | text | eng |
| BrightPonyLongRetrieval | Retrieval | text | eng |
Citation
@inproceedings{su2024bright,
archiveprefix = {arXiv},
author = {Hongjin SU and Howard Yen and Mengzhou Xia and Weijia Shi and Niklas Muennighoff and Han-yu Wang and Liu Haisu and Quan Shi and Zachary S Siegel and Michael Tang and Ruoxi Sun and Jinsung Yoon and Sercan O Arik and Danqi Chen and Tao Yu},
booktitle = {The Thirteenth International Conference on Learning Representations},
eprint = {2407.12883},
title = {{BRIGHT}: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval},
url = {https://openreview.net/forum?id=ykuc5q381b},
year = {2025},
}
BRIGHT-Pro¶
Reasoning-intensive retrieval quality on real-world StackExchange questions, scored against multi-aspect gold evidence. Each query is paired with a long-form reference answer whose cited passages collectively cover several reasoning aspects, so retrievers are measured on surfacing an aspect-diverse evidence set rather than a single relevant passage. Extends BRIGHT with these aspect annotations for agentic search settings.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| BrightProBiologyRetrieval | Retrieval | text | eng |
| BrightProEarthScienceRetrieval | Retrieval | text | eng |
| BrightProEconomicsRetrieval | Retrieval | text | eng |
| BrightProPsychologyRetrieval | Retrieval | text | eng |
| BrightProRoboticsRetrieval | Retrieval | text | eng |
| BrightProStackoverflowRetrieval | Retrieval | text | eng |
| BrightProSustainableLivingRetrieval | Retrieval | text | eng |
Citation
@inproceedings{Zhao2026RethinkingRR,
address = {San Diego, California, United States},
author = {Zhao, Yilun and Wei, Jinbiao and Song, Tingyu and Zhang, Siyue and Zhao, Chen and Cohan, Arman},
booktitle = {Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)},
doi = {10.18653/v1/2026.acl-long.1705},
editor = {Liakata, Maria and Moreira, Viviane P. and Zhang, Jiajun and Jurgens, David},
isbn = {979-8-89176-390-6},
month = {jul},
pages = {36776--36806},
publisher = {Association for Computational Linguistics},
title = {Rethinking Reasoning-Intensive Retrieval: Evaluating and Advancing Retrievers in Agentic Search Systems},
url = {https://aclanthology.org/2026.acl-long.1705/},
year = {2026},
}
BuiltBench(eng)¶
Text embedding quality in the built environment domain across clustering, retrieval, and reranking, spanning architecture, engineering, construction, and operations management.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| BuiltBenchClusteringP2P | Clustering | text | eng |
| BuiltBenchClusteringS2S | Clustering | text | eng |
| BuiltBenchRetrieval | Retrieval | text | eng |
| BuiltBenchReranking | Reranking | text | eng |
Citation
@article{shahinmoghadam2024benchmarking,
author = {Shahinmoghadam, Mehrzad and Motamedi, Ali},
doi = {10.1038/s41598-025-09052-5},
issn = {2045-2322},
journal = {Scientific Reports},
month = {July},
number = {1},
publisher = {Springer Science and Business Media LLC},
title = {Benchmarking pre-trained text embedding models in aligning built asset information},
url = {https://doi.org/10.1038/s41598-025-09052-5},
volume = {15},
year = {2025},
}
ChemTEB¶
Chemical domain text embedding quality across bitext mining, classification, clustering, pair classification, and retrieval.
Tasks
Citation
@inproceedings{kasmaee2024chemteb,
archiveprefix = {arXiv},
author = {Ali Shiraee Kasmaee and Mohammad Khodadad and Mohammad Arshi Saloot and Nick Sherck and Stephen Dokas and Hamidreza Mahyar and Soheila Samiee},
booktitle = {ENLSP},
eprint = {2412.00532},
pages = {512-531},
title = {ChemTEB: Chemical Text Embedding Benchmark, an Overview of Embedding Models Performance & Efficiency on a Specific Domain},
url = {https://proceedings.mlr.press/v262/shiraee-kasmaee24a.html},
year = {2024},
}
ChemTEB(v1.1)¶
Chemical domain text embedding quality across bitext mining, classification, clustering, pair classification, and retrieval. v1.1 adds the ChemRxivRetrieval task.
Tasks
Citation
@inproceedings{kasmaee2024chemteb,
archiveprefix = {arXiv},
author = {Ali Shiraee Kasmaee and Mohammad Khodadad and Mohammad Arshi Saloot and Nick Sherck and Stephen Dokas and Hamidreza Mahyar and Soheila Samiee},
booktitle = {ENLSP},
eprint = {2412.00532},
pages = {512-531},
title = {ChemTEB: Chemical Text Embedding Benchmark, an Overview of Embedding Models Performance & Efficiency on a Specific Domain},
url = {https://proceedings.mlr.press/v262/shiraee-kasmaee24a.html},
year = {2024},
}
@article{kasmaee2025chembed,
author = {Kasmaee, Ali Shiraee and Khodadad, Mohammad and Astaraki, Mahdi and Saloot, Mohammad Arshi and Sherck, Nicholas and Mahyar, Hamidreza and Samiee, Soheila},
journal = {arXiv preprint arXiv:2508.01643},
title = {Chembed: Enhancing chemical literature search through domain-specific text embeddings},
year = {2025},
}
CoIR¶
Code information retrieval across diverse programming languages and coding tasks, including code search, question answering, and text-to-SQL retrieval.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| AppsRetrieval | Retrieval | text | eng, python |
| CodeFeedbackMT | Retrieval | text | eng |
| CodeFeedbackST | Retrieval | text | eng |
| CodeSearchNetCCRetrieval | Retrieval | text | go, java, javascript, php, python, ... (6) |
| CodeTransOceanContest | Retrieval | text | c++, python |
| CodeTransOceanDL | Retrieval | text | python |
| CosQA | Retrieval | text | eng, python |
| COIRCodeSearchNetRetrieval | Retrieval | text | go, java, javascript, php, python, ... (6) |
| StackOverflowQA | Retrieval | text | eng |
| SyntheticText2SQL | Retrieval | text | eng, sql |
Citation
@inproceedings{li2024coircomprehensivebenchmarkcode,
address = {Vienna, Austria},
author = {Li, Xiangyang and Dong, Kuicai and Lee, Yi Quan and Xia, Wei and Zhang, Hao and Dai, Xinyi and Wang, Yasheng and Tang, Ruiming},
booktitle = {Proceedings of the 63rd Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)},
doi = {10.18653/v1/2025.acl-long.1072},
editor = {Che, Wanxiang and Nabende, Joyce and Shutova, Ekaterina and Pilehvar, Mohammad Taher},
isbn = {979-8-89176-251-0},
month = {jul},
pages = {22074--22091},
publisher = {Association for Computational Linguistics},
title = {{C}o{IR}: A Comprehensive Benchmark for Code Information Retrieval Models},
url = {https://aclanthology.org/2025.acl-long.1072/},
year = {2025},
}
CoREB(v1)¶
Code embedding and reranking quality across code-to-text, text-to-code, and code-to-code retrieval tasks, using counterfactually rewritten problems in five programming languages to limit training data contamination.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| CorebC2TRetrieval | Retrieval | text | c++, eng, go, java, python, ... (6) |
| CorebC2CRetrieval | Retrieval | text | c++, eng, go, java, python, ... (6) |
| CorebT2CRetrieval | Retrieval | text | c++, eng, go, java, python, ... (6) |
| CorebC2TReranking | Reranking | text | c++, eng, go, java, python, ... (6) |
| CorebC2CReranking | Reranking | text | c++, eng, go, java, python, ... (6) |
| CorebT2CReranking | Reranking | text | c++, eng, go, java, python, ... (6) |
Citation
@article{xue2026coreb,
author = {Xue, Siqiao and Liao, Zihan and Qin, Jin and Zhang, Ziyin and Mu, Yixiang and Zhou, Fan and Yu, Hang},
journal = {arXiv preprint arXiv:2605.04615},
title = {Beyond Retrieval: A Multitask Benchmark and Model for Code Search},
url = {https://arxiv.org/abs/2605.04615},
year = {2026},
}
CodeRAG¶
Code retrieval quality for retrieval-augmented generation, covering programming solutions, online tutorials, library documentation, and Stack Overflow posts.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| CodeRAGLibraryDocumentationSolutions | Reranking | text | python |
| CodeRAGOnlineTutorials | Reranking | text | python |
| CodeRAGProgrammingSolutions | Reranking | text | python |
| CodeRAGStackoverflowPosts | Reranking | text | python |
Citation
@inproceedings{wang2024coderagbenchretrievalaugmentcode,
address = {Albuquerque, New Mexico},
author = {Wang, Zora Zhiruo and Asai, Akari and Yu, Xinyan Velocity and Xu, Frank F. and Xie, Yiqing and Neubig, Graham and Fried, Daniel},
booktitle = {Findings of the {A}ssociation for {C}omputational {L}inguistics: {NAACL} 2025},
doi = {10.18653/v1/2025.findings-naacl.176},
editor = {Chiruzzo, Luis and Ritter, Alan and Wang, Lu},
isbn = {979-8-89176-195-7},
month = {apr},
pages = {3199--3214},
publisher = {Association for Computational Linguistics},
title = {{C}ode{RAG}-Bench: Can Retrieval Augment Code Generation?},
url = {https://aclanthology.org/2025.findings-naacl.176/},
year = {2025},
}
Encodechka¶
Russian text embedding quality across paraphrase identification, sentiment analysis, toxicity classification, intent classification, natural language inference, and semantic similarity.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| RUParaPhraserSTS | STS | text | rus |
| SentiRuEval2016 | Classification | text | rus |
| RuToxicOKMLCUPClassification | Classification | text | rus |
| InappropriatenessClassificationv2 | Classification | text | rus |
| RuNLUIntentClassification | Classification | text | eng, rus |
| XNLI | PairClassification | text | ara, bul, deu, ell, eng, ... (14) |
| RuSTSBenchmarkSTS | STS | text | rus |
FollowIR¶
Instruction-following retrieval quality, measuring how well models retrieve relevant documents when given detailed natural language instructions alongside queries.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| Robust04InstructionRetrieval | InstructionReranking | text | eng |
| News21InstructionRetrieval | InstructionReranking | text | eng |
| Core17InstructionRetrieval | InstructionReranking | text | eng |
Citation
@inproceedings{weller2024followir,
address = {Albuquerque, New Mexico},
author = {Weller, Orion and Chang, Benjamin and MacAvaney, Sean and Lo, Kyle and Cohan, Arman and Van Durme, Benjamin and Lawrie, Dawn and Soldaini, Luca},
booktitle = {Proceedings of the 2025 Conference of the Nations of the {A}mericas Chapter of the {A}ssociation for {C}omputational {L}inguistics: Human Language Technologies (Volume 1: Long Papers)},
doi = {10.18653/v1/2025.naacl-long.597},
editor = {Chiruzzo, Luis and Ritter, Alan and Wang, Lu},
isbn = {979-8-89176-189-6},
month = {apr},
pages = {11926--11942},
publisher = {Association for Computational Linguistics},
title = {{F}ollow{IR}: Evaluating and Teaching Information Retrieval Models to Follow Instructions},
url = {https://aclanthology.org/2025.naacl-long.597/},
year = {2025},
}
HUME(v1)¶
Text embedding performance benchmarked against human annotator scores across classification, clustering, reranking, and semantic similarity tasks, capturing where models exceed or fall short of human-level judgment.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| HUMEEmotionClassification | Classification | text | eng |
| HUMEToxicConversationsClassification | Classification | text | eng |
| HUMETweetSentimentExtractionClassification | Classification | text | eng |
| HUMEMultilingualSentimentClassification | Classification | text | ara, eng, nob, rus |
| HUMEArxivClusteringP2P | Clustering | text | eng |
| HUMERedditClusteringP2P | Clustering | text | eng |
| HUMEWikiCitiesClustering | Clustering | text | eng |
| HUMESIB200ClusteringS2S | Clustering | text | ara, dan, eng, fra, rus |
| HUMECore17InstructionReranking | Reranking | text | eng |
| HUMENews21InstructionReranking | Reranking | text | eng |
| HUMERobust04InstructionReranking | Reranking | text | eng |
| HUMEWikipediaRerankingMultilingual | Reranking | text | dan, eng, nob |
| HUMESICK-R | STS | text | eng |
| HUMESTS12 | STS | text | eng |
| HUMESTSBenchmark | STS | text | eng |
| HUMESTS22 | STS | text | ara, eng, fra, rus |
IFIR¶
Instruction-following retrieval quality in expert domains including healthcare, finance, and legal, where queries are paired with domain-specific natural language instructions.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| IFIRAila | InstructionRetrieval | text | eng |
| IFIRCds | InstructionRetrieval | text | eng |
| IFIRFiQA | InstructionRetrieval | text | eng |
| IFIRFire | InstructionRetrieval | text | eng |
| IFIRNFCorpus | InstructionRetrieval | text | eng |
| IFIRPm | InstructionRetrieval | text | eng |
| IFIRScifact | InstructionRetrieval | text | eng |
Citation
@inproceedings{song2025ifir,
author = {Song, Tingyu and Gan, Guo and Shang, Mingsheng and Zhao, Yilun},
booktitle = {Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)},
pages = {10186--10204},
title = {IFIR: A Comprehensive Benchmark for Evaluating Instruction-Following in Expert-Domain Information Retrieval},
year = {2025},
}
JMTEB(v2)¶
Japanese text embedding quality across clustering, classification, semantic similarity, retrieval, and reranking. v2 extends the benchmark to 28 datasets for more comprehensive evaluation compared with MTEB(jpn, v1).
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| LivedoorNewsClustering.v2 | Clustering | text | jpn |
| MewsC16JaClustering | Clustering | text | jpn |
| SIB200ClusteringS2S | Clustering | text | ace, acm, acq, aeb, afr, ... (197) |
| AmazonReviewsClassification | Classification | text | cmn, deu, eng, fra, jpn, ... (6) |
| AmazonCounterfactualClassification | Classification | text | deu, eng, jpn |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MassiveScenarioClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| JapaneseSentimentClassification | Classification | text | jpn |
| SIB200Classification | Classification | text | ace, acm, acq, aeb, afr, ... (197) |
| WRIMEClassification | Classification | text | jpn |
| JSTS | STS | text | jpn |
| JSICK | STS | text | jpn |
| JaqketRetrieval | Retrieval | text | jpn |
| MrTidyRetrieval | Retrieval | text | ara, ben, eng, fin, ind, ... (11) |
| JaGovFaqsRetrieval | Retrieval | text | jpn |
| NLPJournalTitleAbsRetrieval.V2 | Retrieval | text | jpn |
| NLPJournalTitleIntroRetrieval.V2 | Retrieval | text | jpn |
| NLPJournalAbsIntroRetrieval.V2 | Retrieval | text | jpn |
| NLPJournalAbsArticleRetrieval.V2 | Retrieval | text | jpn |
| JaCWIRRetrieval | Retrieval | text | jpn |
| MIRACLRetrieval | Retrieval | text | ara, ben, deu, eng, fas, ... (18) |
| MintakaRetrieval | Retrieval | text | ara, deu, fra, hin, ita, ... (8) |
| MultiLongDocRetrieval | Retrieval | text | ara, cmn, deu, eng, fra, ... (13) |
| ESCIReranking | Reranking | text | eng, jpn, spa |
| JQaRAReranking | Reranking | text | jpn |
| JaCWIRReranking | Reranking | text | jpn |
| MIRACLReranking | Reranking | text | ara, ben, deu, eng, fas, ... (18) |
| MultiLongDocReranking | Reranking | text | ara, deu, eng, fra, hin, ... (13) |
Citation
@inproceedings{li-etal-2026-jmteb,
address = {Palma de Mallorca, Spain},
author = {Li, Shengzhe and Ohagi, Masaya and Ri, Ryokan and Fukuchi, Akihiko and Shibata, Tomohide and Kawahara, Daisuke},
booktitle = {Proceedings of the Fifteenth Language Resources and Evaluation Conference},
doi = {10.63317/5ouzpv2f2f6k},
month = may,
pages = {7423--7434},
publisher = {ELRA Language Resource Association},
title = {{JMTEB} and {JMTEB}-lite: {J}apanese Massive Text Embedding Benchmark and Its Lightweight Version},
url = {https://aclanthology.org/2026.lrec-1.588/},
year = {2026},
}
JMTEB-lite(v1)¶
Japanese text embedding quality across clustering, classification, semantic similarity, retrieval, and reranking, with heavy datasets optimized via hard negative pooling to enable faster evaluation while maintaining rankings consistent with JMTEB.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| LivedoorNewsClustering.v2 | Clustering | text | jpn |
| MewsC16JaClustering | Clustering | text | jpn |
| SIB200ClusteringS2S | Clustering | text | ace, acm, acq, aeb, afr, ... (197) |
| AmazonReviewsClassification | Classification | text | cmn, deu, eng, fra, jpn, ... (6) |
| AmazonCounterfactualClassification | Classification | text | deu, eng, jpn |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MassiveScenarioClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| JapaneseSentimentClassification | Classification | text | jpn |
| SIB200Classification | Classification | text | ace, acm, acq, aeb, afr, ... (197) |
| WRIMEClassification | Classification | text | jpn |
| JSTS | STS | text | jpn |
| JSICK | STS | text | jpn |
| JaqketRetrievalLite | Retrieval | text | jpn |
| MrTyDiJaRetrievalLite | Retrieval | text | jpn |
| JaGovFaqsRetrieval | Retrieval | text | jpn |
| NLPJournalTitleAbsRetrieval.V2 | Retrieval | text | jpn |
| NLPJournalTitleIntroRetrieval.V2 | Retrieval | text | jpn |
| NLPJournalAbsIntroRetrieval.V2 | Retrieval | text | jpn |
| NLPJournalAbsArticleRetrieval.V2 | Retrieval | text | jpn |
| JaCWIRRetrievalLite | Retrieval | text | jpn |
| MIRACLJaRetrievalLite | Retrieval | text | jpn |
| MintakaRetrieval | Retrieval | text | ara, deu, fra, hin, ita, ... (8) |
| MultiLongDocRetrieval | Retrieval | text | ara, cmn, deu, eng, fra, ... (13) |
| ESCIReranking | Reranking | text | eng, jpn, spa |
| JQaRARerankingLite | Reranking | text | jpn |
| JaCWIRRerankingLite | Reranking | text | jpn |
| MIRACLReranking | Reranking | text | ara, ben, deu, eng, fas, ... (18) |
| MultiLongDocReranking | Reranking | text | ara, deu, eng, fra, hin, ... (13) |
Citation
@inproceedings{li-etal-2026-jmteb,
address = {Palma de Mallorca, Spain},
author = {Li, Shengzhe and Ohagi, Masaya and Ri, Ryokan and Fukuchi, Akihiko and Shibata, Tomohide and Kawahara, Daisuke},
booktitle = {Proceedings of the Fifteenth Language Resources and Evaluation Conference},
doi = {10.63317/5ouzpv2f2f6k},
month = may,
pages = {7423--7434},
publisher = {ELRA Language Resource Association},
title = {{JMTEB} and {JMTEB}-lite: {J}apanese Massive Text Embedding Benchmark and Its Lightweight Version},
url = {https://aclanthology.org/2026.lrec-1.588/},
year = {2026},
}
JinaVDR¶
Visual document retrieval across multilingual, domain-diverse, and layout-rich document types, spanning medical, legal, financial, technical, and other domains across multiple languages.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| JinaVDRMedicalPrescriptionsRetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRStanfordSlideRetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRDonutVQAISynHMPRetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRTableVQARetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRChartQARetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRTQARetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDROpenAINewsRetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDREuropeanaDeNewsRetrieval | DocumentUnderstanding | text, image | deu |
| JinaVDREuropeanaEsNewsRetrieval | DocumentUnderstanding | text, image | spa |
| JinaVDREuropeanaItScansRetrieval | DocumentUnderstanding | text, image | ita |
| JinaVDREuropeanaNlLegalRetrieval | DocumentUnderstanding | text, image | nld |
| JinaVDRHindiGovVQARetrieval | DocumentUnderstanding | text, image | hin |
| JinaVDRAutomobileCatelogRetrieval | DocumentUnderstanding | text, image | jpn |
| JinaVDRBeveragesCatalogueRetrieval | DocumentUnderstanding | text, image | rus |
| JinaVDRRamensBenchmarkRetrieval | DocumentUnderstanding | text, image | jpn |
| JinaVDRJDocQARetrieval | DocumentUnderstanding | text, image | jpn |
| JinaVDRHungarianDocQARetrieval | DocumentUnderstanding | text, image | hun |
| JinaVDRArabicChartQARetrieval | DocumentUnderstanding | text, image | ara |
| JinaVDRArabicInfographicsVQARetrieval | DocumentUnderstanding | text, image | ara |
| JinaVDROWIDChartsRetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRMPMQARetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRJina2024YearlyBookRetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRWikimediaCommonsMapsRetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRPlotQARetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRMMTabRetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRCharXivOCRRetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRStudentEnrollmentSyntheticRetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRGitHubReadmeRetrieval | DocumentUnderstanding | text, image | ara, ben, deu, eng, fra, ... (17) |
| JinaVDRTweetStockSyntheticsRetrieval | DocumentUnderstanding | text, image | ara, deu, eng, fra, hin, ... (10) |
| JinaVDRAirbnbSyntheticRetrieval | DocumentUnderstanding | text, image | ara, deu, eng, fra, hin, ... (10) |
| JinaVDRShanghaiMasterPlanRetrieval | DocumentUnderstanding | text, image | zho |
| JinaVDRWikimediaCommonsDocumentsRetrieval | DocumentUnderstanding | text, image | ara, ben, deu, eng, fra, ... (20) |
| JinaVDREuropeanaFrNewsRetrieval | DocumentUnderstanding | text, image | fra |
| JinaVDRDocQAHealthcareIndustryRetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRDocQAAI | DocumentUnderstanding | text, image | eng |
| JinaVDRShiftProjectRetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRTatQARetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRInfovqaRetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRDocVQARetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRDocQAGovReportRetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRTabFQuadRetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRDocQAEnergyRetrieval | DocumentUnderstanding | text, image | eng |
| JinaVDRArxivQARetrieval | DocumentUnderstanding | text, image | eng |
Citation
@inproceedings{günther2025jinaembeddingsv4universalembeddingsmultimodal,
address = {Suzhuo, China},
author = {G{\"u}nther, Michael and Sturua, Saba and Akram, Mohammad Kalim and Mohr, Isabelle and Ungureanu, Andrei and Wang, Bo and Eslami, Sedigheh and Martens, Scott and Werk, Maximilian and Wang, Nan and Xiao, Han},
booktitle = {Proceedings of the 5th Workshop on Multilingual Representation Learning ({MRL} 2025)},
doi = {10.18653/v1/2025.mrl-main.36},
editor = {Adelani, David Ifeoluwa and Arnett, Catherine and Ataman, Duygu and Chang, Tyler A. and Gonen, Hila and Raja, Rahul and Schmidt, Fabian and Stap, David and Wang, Jiayi},
isbn = {979-8-89176-345-6},
month = {nov},
pages = {531--550},
publisher = {Association for Computational Linguistics},
title = {jina-embeddings-v4: Universal Embeddings for Multimodal Multilingual Retrieval},
url = {https://aclanthology.org/2025.mrl-main.36/},
year = {2025},
}
KoViDoRe(v2)¶
Korean visual document retrieval across enterprise document domains including cybersecurity, economics, energy, and HR.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| KoVidore2CybersecurityRetrieval | DocumentUnderstanding | text, image | kor |
| KoVidore2EconomicRetrieval | DocumentUnderstanding | text, image | kor |
| KoVidore2EnergyRetrieval | DocumentUnderstanding | text, image | kor |
| KoVidore2HrRetrieval | DocumentUnderstanding | text, image | kor |
Citation
@inproceedings{choi-etal-2026-kovidore,
address = {San Diego, USA},
author = {Choi, Yongbin and
Song, Yongwoo and
Sung, Mujeen},
booktitle = {Proceedings of the 2nd Workshop on Multimodal Augmented Generation via Multimodal Retrieval ({MAGM}a{R} 2026)},
doi = {10.18653/v1/2026.magmar-main.11},
editor = {Murray, Kenton and
Kriz, Reno},
isbn = {979-8-89176-425-5},
month = jul,
pages = {54--80},
publisher = {Association for Computational Linguistics},
title = {{K}o{V}i{D}o{R}e: A Benchmark for {K}orean Visual Document Retrieval},
url = {https://aclanthology.org/2026.magmar-main.11/},
year = {2026},
}
LMEB¶
Long-horizon memory retrieval quality across episodic, dialogue, semantic, and procedural retrieval tasks, measuring how well embedding models retrieve evidence in long-term memory scenarios.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| EPBench | Retrieval | text | eng |
| KnowMeBench | Retrieval | text | eng |
| LoCoMo | Retrieval | text | eng |
| LongMemEval | Retrieval | text | eng |
| REALTALK | Retrieval | text | eng |
| TMD | Retrieval | text | eng |
| MemBench | Retrieval | text | eng |
| ConvoMem | Retrieval | text | eng |
| QASPER | Retrieval | text | eng |
| NovelQA | Retrieval | text | eng |
| PeerQA | Retrieval | text | eng |
| CovidQA | Retrieval | text | eng |
| ESGReports | Retrieval | text | eng |
| LMEBMLDR | Retrieval | text | eng |
| LooGLE | Retrieval | text | eng |
| LMEB_SciFact | Retrieval | text | eng |
| Gorilla | Retrieval | text | eng |
| ToolBench | Retrieval | text | eng |
| ReMe | Retrieval | text | eng |
| ProceduralMemBench | Retrieval | text | eng |
| MemGovern | Retrieval | text | eng |
| DeepPlanning | Retrieval | text | eng |
Citation
@misc{zhao2026lmeb,
archiveprefix = {arXiv},
author = {Zhao, Xinping and Hu, Xinshuo and Xu, Jiaxin and Tang, Danyu and Zhang, Xin and Zhou, Mengjia and Zhong, Yan and Zhou, Yao and Shan, Zifei and Zhang, Meishan and Hu, Baotian and Zhang, Min},
eprint = {2603.12572},
primaryclass = {cs.CL},
title = {LMEB: Long-horizon Memory Embedding Benchmark},
url = {https://arxiv.org/abs/2603.12572},
year = {2026},
}
LongEmbed¶
Long-context retrieval quality across synthetic and real-world tasks featuring documents of varying length with dispersed target information.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| LEMBNarrativeQARetrieval | Retrieval | text | eng |
| LEMBNeedleRetrieval | Retrieval | text | eng |
| LEMBPasskeyRetrieval | Retrieval | text | eng |
| LEMBQMSumRetrieval | Retrieval | text | eng |
| LEMBSummScreenFDRetrieval | Retrieval | text | eng |
| LEMBWikimQARetrieval | Retrieval | text | eng |
Citation
@inproceedings{zhu2024longembed,
address = {Miami, Florida, USA},
author = {Zhu, Dawei and Wang, Liang and Yang, Nan and Song, Yifan and Wu, Wenhao and Wei, Furu and Li, Sujian},
booktitle = {Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing},
doi = {10.18653/v1/2024.emnlp-main.47},
editor = {Al-Onaizan, Yaser and Bansal, Mohit and Chen, Yun-Nung},
month = {nov},
pages = {802--816},
publisher = {Association for Computational Linguistics},
title = {{L}ong{E}mbed: Extending Embedding Models for Long Context Retrieval},
url = {https://aclanthology.org/2024.emnlp-main.47/},
year = {2024},
}
MAEB(v1)¶
Audio embedding quality across both audio-only and audio-text cross-modal tasks, spanning retrieval, classification, clustering, multilabel classification, pair classification, reranking, and zero-shot classification.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| ClothoT2ARetrieval | Any2AnyRetrieval | text, audio | eng |
| CommonVoiceMini21T2ARetrieval | Any2AnyRetrieval | text, audio | abk, afr, amh, ara, asm, ... (114) |
| FleursT2ARetrieval | Any2AnyRetrieval | text, audio | afr, amh, ara, asm, ast, ... (102) |
| GigaSpeechT2ARetrieval | Any2AnyRetrieval | text, audio | eng |
| JamAltArtistA2ARetrieval | Any2AnyRetrieval | audio | deu, eng, fra, spa |
| JamAltLyricA2TRetrieval | Any2AnyRetrieval | text, audio | deu, eng, fra, spa |
| MACST2ARetrieval | Any2AnyRetrieval | text, audio | eng |
| SpokenSQuADT2ARetrieval | Any2AnyRetrieval | text, audio | eng |
| UrbanSound8KT2ARetrieval | Any2AnyRetrieval | text, audio | zxx |
| BeijingOpera | AudioClassification | audio | zxx |
| BirdCLEF | AudioClassification | audio | zxx |
| CREMA_D | AudioClassification | audio | eng |
| CommonLanguageAgeDetection | AudioClassification | audio | eng |
| GTZANGenre | AudioClassification | audio | zxx |
| IEMOCAPGender | AudioClassification | audio | eng |
| MInDS14 | AudioClassification | audio | ces, deu, eng, fra, ita, ... (12) |
| MridinghamTonic | AudioClassification | audio | zxx |
| SIBFLEURS | AudioClassification | audio | afr, amh, arb, asm, ast, ... (101) |
| VoxCelebSA | AudioClassification | audio | eng |
| VoxPopuliLanguageID | AudioClassification | audio | deu, eng, fra, pol, spa |
| CREMA_DClustering | AudioClustering | audio | eng |
| VehicleSoundClustering | AudioClustering | audio | zxx |
| VoxPopuliGenderClustering | AudioClustering | audio | deu, eng, fra, pol, spa |
| CREMADPairClassification | AudioPairClassification | audio | eng |
| NMSQAPairClassification | AudioPairClassification | audio | eng |
| VoxPopuliAccentPairClassification | AudioPairClassification | audio | eng |
| GTZANAudioReranking | AudioReranking | audio | zxx |
| RavdessZeroshot | AudioZeroshotClassification | audio, text | eng |
| SpeechCommandsZeroshotv0.02 | AudioZeroshotClassification | audio, text | eng |
| FSD2019Kaggle | AudioMultilabelClassification | audio | eng |
Citation
@misc{assadi2026maebmassiveaudioembedding,
archiveprefix = {arXiv},
author = {Adnan El Assadi and Isaac Chung and Chenghao Xiao and Roman Solomatin and Animesh Jha and Rahul Chand and Silky Singh and Kaitlyn Wang and Ali Sartaz Khan and Marc Moussa Nasser and Sufen Fong and Pengfei He and Alan Xiao and Ayush Sunil Munot and Aditya Shrivastava and Artem Gazizov and Niklas Muennighoff and Kenneth Enevoldsen},
eprint = {2602.16008},
primaryclass = {cs.SD},
title = {MAEB: Massive Audio Embedding Benchmark},
url = {https://arxiv.org/abs/2602.16008},
year = {2026},
}
MAEB(v1, audio-only)¶
Audio-only embedding quality across classification, clustering, pair classification, reranking, and retrieval tasks.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| JamAltArtistA2ARetrieval | Any2AnyRetrieval | audio | deu, eng, fra, spa |
| BeijingOpera | AudioClassification | audio | zxx |
| BirdCLEF | AudioClassification | audio | zxx |
| CREMA_D | AudioClassification | audio | eng |
| CommonLanguageAgeDetection | AudioClassification | audio | eng |
| GTZANGenre | AudioClassification | audio | zxx |
| IEMOCAPGender | AudioClassification | audio | eng |
| MInDS14 | AudioClassification | audio | ces, deu, eng, fra, ita, ... (12) |
| MridinghamTonic | AudioClassification | audio | zxx |
| SIBFLEURS | AudioClassification | audio | afr, amh, arb, asm, ast, ... (101) |
| VoxCelebSA | AudioClassification | audio | eng |
| VoxPopuliLanguageID | AudioClassification | audio | deu, eng, fra, pol, spa |
| CREMA_DClustering | AudioClustering | audio | eng |
| VehicleSoundClustering | AudioClustering | audio | zxx |
| VoxPopuliGenderClustering | AudioClustering | audio | deu, eng, fra, pol, spa |
| CREMADPairClassification | AudioPairClassification | audio | eng |
| NMSQAPairClassification | AudioPairClassification | audio | eng |
| VoxPopuliAccentPairClassification | AudioPairClassification | audio | eng |
| GTZANAudioReranking | AudioReranking | audio | zxx |
Citation
@misc{assadi2026maebmassiveaudioembedding,
archiveprefix = {arXiv},
author = {Adnan El Assadi and Isaac Chung and Chenghao Xiao and Roman Solomatin and Animesh Jha and Rahul Chand and Silky Singh and Kaitlyn Wang and Ali Sartaz Khan and Marc Moussa Nasser and Sufen Fong and Pengfei He and Alan Xiao and Ayush Sunil Munot and Aditya Shrivastava and Artem Gazizov and Niklas Muennighoff and Kenneth Enevoldsen},
eprint = {2602.16008},
primaryclass = {cs.SD},
title = {MAEB: Massive Audio Embedding Benchmark},
url = {https://arxiv.org/abs/2602.16008},
year = {2026},
}
MIEB(Img)¶
Image-only embedding quality across retrieval, classification, clustering, and visual STS, excluding tasks that require a text encoder.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| CUB200I2IRetrieval | Any2AnyRetrieval | image | eng |
| FORBI2IRetrieval | Any2AnyRetrieval | image | eng |
| GLDv2I2IRetrieval | Any2AnyRetrieval | image | eng |
| METI2IRetrieval | Any2AnyRetrieval | image | eng |
| NIGHTSI2IRetrieval | Any2AnyRetrieval | image | eng |
| ROxfordEasyI2IRetrieval | Any2AnyRetrieval | image | eng |
| ROxfordMediumI2IRetrieval | Any2AnyRetrieval | image | eng |
| ROxfordHardI2IRetrieval | Any2AnyRetrieval | image | eng |
| RP2kI2IRetrieval | Any2AnyRetrieval | image | eng |
| RParisEasyI2IRetrieval | Any2AnyRetrieval | image | eng |
| RParisMediumI2IRetrieval | Any2AnyRetrieval | image | eng |
| RParisHardI2IRetrieval | Any2AnyRetrieval | image | eng |
| SketchyI2IRetrieval | Any2AnyRetrieval | image | eng |
| SOPI2IRetrieval | Any2AnyRetrieval | image | eng |
| StanfordCarsI2IRetrieval | Any2AnyRetrieval | image | eng |
| Birdsnap | ImageClassification | image | eng |
| Caltech101 | ImageClassification | image | eng |
| CIFAR10 | ImageClassification | image | eng |
| CIFAR100 | ImageClassification | image | eng |
| Country211 | ImageClassification | image | eng |
| DTD | ImageClassification | image | eng |
| EuroSAT | ImageClassification | image | eng |
| FER2013 | ImageClassification | image | eng |
| FGVCAircraft | ImageClassification | image | eng |
| Food101Classification | ImageClassification | image | eng |
| GTSRB | ImageClassification | image | eng |
| Imagenet1k | ImageClassification | image | eng |
| MNIST | ImageClassification | image | eng |
| OxfordFlowersClassification | ImageClassification | image | eng |
| OxfordPets | ImageClassification | image | eng |
| PatchCamelyon | ImageClassification | image | eng |
| RESISC45 | ImageClassification | image | eng |
| StanfordCars | ImageClassification | image | eng |
| STL10 | ImageClassification | image | eng |
| SUN397 | ImageClassification | image | eng |
| UCF101 | ImageClassification | image | eng |
| CIFAR10Clustering | ImageClustering | image | eng |
| CIFAR100Clustering | ImageClustering | image | eng |
| ImageNetDog15Clustering | ImageClustering | image | eng |
| ImageNet10Clustering | ImageClustering | image | eng |
| TinyImageNetClustering | ImageClustering | image | eng |
| VOC2007 | ImageClassification | image | eng |
| STS12VisualSTS | VisualSTS(eng) | image | eng |
| STS13VisualSTS | VisualSTS(eng) | image | eng |
| STS14VisualSTS | VisualSTS(eng) | image | eng |
| STS15VisualSTS | VisualSTS(eng) | image | eng |
| STS16VisualSTS | VisualSTS(eng) | image | eng |
| STS17MultilingualVisualSTS | VisualSTS(multi) | image | ara, deu, eng, fra, ita, ... (9) |
| STSBenchmarkMultilingualVisualSTS | VisualSTS(multi) | image | cmn, deu, eng, fra, ita, ... (10) |
Citation
@inproceedings{xiao2025mieb,
author = {Xiao, Chenghao and Chung, Isaac and Kerboua, Imene and Stirling, Jamie and Zhang, Xin and Kardos, M\'arton and Solomatin, Roman and Al Moubayed, Noura and Enevoldsen, Kenneth and Muennighoff, Niklas},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
pages = {22187-22198},
title = {MIEB: Massive Image Embedding Benchmark},
year = {2025},
}
MIEB(Multilingual)¶
Multilingual image embedding quality across 39 languages, spanning image classification (zero-shot and linear probing), clustering, retrieval, compositionality evaluation, document understanding, visual STS, and CV-centric tasks. Extends MIEB(eng) with multilingual retrieval datasets and the multilingual portions of VisualSTS-b and VisualSTS-16.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| Birdsnap | ImageClassification | image | eng |
| Caltech101 | ImageClassification | image | eng |
| CIFAR10 | ImageClassification | image | eng |
| CIFAR100 | ImageClassification | image | eng |
| Country211 | ImageClassification | image | eng |
| DTD | ImageClassification | image | eng |
| EuroSAT | ImageClassification | image | eng |
| FER2013 | ImageClassification | image | eng |
| FGVCAircraft | ImageClassification | image | eng |
| Food101Classification | ImageClassification | image | eng |
| GTSRB | ImageClassification | image | eng |
| Imagenet1k | ImageClassification | image | eng |
| MNIST | ImageClassification | image | eng |
| OxfordFlowersClassification | ImageClassification | image | eng |
| OxfordPets | ImageClassification | image | eng |
| PatchCamelyon | ImageClassification | image | eng |
| RESISC45 | ImageClassification | image | eng |
| StanfordCars | ImageClassification | image | eng |
| STL10 | ImageClassification | image | eng |
| SUN397 | ImageClassification | image | eng |
| UCF101 | ImageClassification | image | eng |
| VOC2007 | ImageClassification | image | eng |
| CIFAR10Clustering | ImageClustering | image | eng |
| CIFAR100Clustering | ImageClustering | image | eng |
| ImageNetDog15Clustering | ImageClustering | image | eng |
| ImageNet10Clustering | ImageClustering | image | eng |
| TinyImageNetClustering | ImageClustering | image | eng |
| BirdsnapZeroShot | ZeroShotClassification | image, text | eng |
| Caltech101ZeroShot | ZeroShotClassification | text, image | eng |
| CIFAR10ZeroShot | ZeroShotClassification | text, image | eng |
| CIFAR100ZeroShot | ZeroShotClassification | text, image | eng |
| CLEVRZeroShot | ZeroShotClassification | text, image | eng |
| CLEVRCountZeroShot | ZeroShotClassification | text, image | eng |
| Country211ZeroShot | ZeroShotClassification | image, text | eng |
| DTDZeroShot | ZeroShotClassification | image, text | eng |
| EuroSATZeroShot | ZeroShotClassification | image, text | eng |
| FER2013ZeroShot | ZeroShotClassification | image, text | eng |
| FGVCAircraftZeroShot | ZeroShotClassification | text, image | eng |
| Food101ZeroShot | ZeroShotClassification | text, image | eng |
| GTSRBZeroShot | ZeroShotClassification | image, text | eng |
| Imagenet1kZeroShot | ZeroShotClassification | image, text | eng |
| MNISTZeroShot | ZeroShotClassification | image, text | eng |
| OxfordPetsZeroShot | ZeroShotClassification | text, image | eng |
| PatchCamelyonZeroShot | ZeroShotClassification | image, text | eng |
| RenderedSST2 | ZeroShotClassification | text, image | eng |
| RESISC45ZeroShot | ZeroShotClassification | image, text | eng |
| StanfordCarsZeroShot | ZeroShotClassification | image, text | eng |
| STL10ZeroShot | ZeroShotClassification | image, text | eng |
| SUN397ZeroShot | ZeroShotClassification | image, text | eng |
| UCF101ZeroShot | ZeroShotClassification | image, text | eng |
| BLINKIT2IMultiChoice | VisionCentricQA | text, image | eng |
| BLINKIT2TMultiChoice | VisionCentricQA | text, image | eng |
| CVBenchCount | VisionCentricQA | image, text | eng |
| CVBenchRelation | VisionCentricQA | text, image | eng |
| CVBenchDepth | VisionCentricQA | text, image | eng |
| CVBenchDistance | VisionCentricQA | text, image | eng |
| AROCocoOrder | Compositionality | text, image | eng |
| AROFlickrOrder | Compositionality | text, image | eng |
| AROVisualAttribution | Compositionality | text, image | eng |
| AROVisualRelation | Compositionality | text, image | eng |
| SugarCrepe | Compositionality | text, image | eng |
| Winoground | Compositionality | text, image | eng |
| ImageCoDe | Compositionality | text, image | eng |
| STS12VisualSTS | VisualSTS(eng) | image | eng |
| STS13VisualSTS | VisualSTS(eng) | image | eng |
| STS14VisualSTS | VisualSTS(eng) | image | eng |
| STS15VisualSTS | VisualSTS(eng) | image | eng |
| STS16VisualSTS | VisualSTS(eng) | image | eng |
| BLINKIT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| BLINKIT2TRetrieval | Any2AnyRetrieval | text, image | eng |
| CIRRIT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| CUB200I2IRetrieval | Any2AnyRetrieval | image | eng |
| EDIST2ITRetrieval | Any2AnyRetrieval | text, image | eng |
| Fashion200kI2TRetrieval | Any2AnyRetrieval | text, image | eng |
| Fashion200kT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| FashionIQIT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| Flickr30kI2TRetrieval | Any2AnyRetrieval | text, image | eng |
| Flickr30kT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| FORBI2IRetrieval | Any2AnyRetrieval | image | eng |
| GLDv2I2IRetrieval | Any2AnyRetrieval | image | eng |
| GLDv2I2TRetrieval | Any2AnyRetrieval | text, image | eng |
| HatefulMemesI2TRetrieval | Any2AnyRetrieval | text, image | eng |
| HatefulMemesT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| ImageCoDeT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| InfoSeekIT2ITRetrieval | Any2AnyRetrieval | text, image | eng |
| InfoSeekIT2TRetrieval | Any2AnyRetrieval | text, image | eng |
| MemotionI2TRetrieval | Any2AnyRetrieval | text, image | eng |
| MemotionT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| METI2IRetrieval | Any2AnyRetrieval | image | eng |
| MSCOCOI2TRetrieval | Any2AnyRetrieval | text, image | eng |
| MSCOCOT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| NIGHTSI2IRetrieval | Any2AnyRetrieval | image | eng |
| OVENIT2ITRetrieval | Any2AnyRetrieval | image, text | eng |
| OVENIT2TRetrieval | Any2AnyRetrieval | text, image | eng |
| ROxfordEasyI2IRetrieval | Any2AnyRetrieval | image | eng |
| ROxfordMediumI2IRetrieval | Any2AnyRetrieval | image | eng |
| ROxfordHardI2IRetrieval | Any2AnyRetrieval | image | eng |
| RP2kI2IRetrieval | Any2AnyRetrieval | image | eng |
| RParisEasyI2IRetrieval | Any2AnyRetrieval | image | eng |
| RParisMediumI2IRetrieval | Any2AnyRetrieval | image | eng |
| RParisHardI2IRetrieval | Any2AnyRetrieval | image | eng |
| SciMMIRI2TRetrieval | Any2AnyRetrieval | text, image | eng |
| SciMMIRT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| SketchyI2IRetrieval | Any2AnyRetrieval | image | eng |
| SOPI2IRetrieval | Any2AnyRetrieval | image | eng |
| StanfordCarsI2IRetrieval | Any2AnyRetrieval | image | eng |
| TUBerlinT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| VidoreArxivQARetrieval | DocumentUnderstanding | text, image | eng |
| VidoreDocVQARetrieval | DocumentUnderstanding | text, image | eng |
| VidoreInfoVQARetrieval | DocumentUnderstanding | text, image | eng |
| VidoreTabfquadRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreTatdqaRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreShiftProjectRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreSyntheticDocQAAIRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreSyntheticDocQAEnergyRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreSyntheticDocQAGovernmentReportsRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreSyntheticDocQAHealthcareIndustryRetrieval | DocumentUnderstanding | text, image | eng |
| VisualNewsI2TRetrieval | Any2AnyRetrieval | image, text | eng |
| VisualNewsT2IRetrieval | Any2AnyRetrieval | image, text | eng |
| VizWizIT2TRetrieval | Any2AnyRetrieval | text, image | eng |
| VQA2IT2TRetrieval | Any2AnyRetrieval | text, image | eng |
| WebQAT2ITRetrieval | Any2AnyRetrieval | image, text | eng |
| WebQAT2TRetrieval | Any2AnyRetrieval | text | eng |
| WITT2IRetrieval | Any2AnyMultilingualRetrieval | text, image | ara, bul, dan, ell, eng, ... (11) |
| XFlickr30kCoT2IRetrieval | Any2AnyMultilingualRetrieval | text, image | deu, eng, ind, jpn, rus, ... (8) |
| XM3600T2IRetrieval | Any2AnyMultilingualRetrieval | text, image | ara, ben, ces, dan, deu, ... (38) |
| VisualSTS17Eng | VisualSTS(eng) | image | ara, deu, eng, fra, ita, ... (9) |
| VisualSTS-b-Eng | VisualSTS(eng) | image | cmn, deu, eng, fra, ita, ... (10) |
| VisualSTS17Multilingual | VisualSTS(multi) | image | ara, deu, eng, fra, ita, ... (9) |
| VisualSTS-b-Multilingual | VisualSTS(multi) | image | cmn, deu, eng, fra, ita, ... (10) |
Citation
@inproceedings{xiao2025mieb,
author = {Xiao, Chenghao and Chung, Isaac and Kerboua, Imene and Stirling, Jamie and Zhang, Xin and Kardos, M\'arton and Solomatin, Roman and Al Moubayed, Noura and Enevoldsen, Kenneth and Muennighoff, Niklas},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
pages = {22187-22198},
title = {MIEB: Massive Image Embedding Benchmark},
year = {2025},
}
MIEB(eng)¶
English image embedding quality across image classification (zero-shot and linear probing), clustering, retrieval, compositionality evaluation, document understanding, visual STS, and CV-centric tasks.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| Birdsnap | ImageClassification | image | eng |
| Caltech101 | ImageClassification | image | eng |
| CIFAR10 | ImageClassification | image | eng |
| CIFAR100 | ImageClassification | image | eng |
| Country211 | ImageClassification | image | eng |
| DTD | ImageClassification | image | eng |
| EuroSAT | ImageClassification | image | eng |
| FER2013 | ImageClassification | image | eng |
| FGVCAircraft | ImageClassification | image | eng |
| Food101Classification | ImageClassification | image | eng |
| GTSRB | ImageClassification | image | eng |
| Imagenet1k | ImageClassification | image | eng |
| MNIST | ImageClassification | image | eng |
| OxfordFlowersClassification | ImageClassification | image | eng |
| OxfordPets | ImageClassification | image | eng |
| PatchCamelyon | ImageClassification | image | eng |
| RESISC45 | ImageClassification | image | eng |
| StanfordCars | ImageClassification | image | eng |
| STL10 | ImageClassification | image | eng |
| SUN397 | ImageClassification | image | eng |
| UCF101 | ImageClassification | image | eng |
| VOC2007 | ImageClassification | image | eng |
| CIFAR10Clustering | ImageClustering | image | eng |
| CIFAR100Clustering | ImageClustering | image | eng |
| ImageNetDog15Clustering | ImageClustering | image | eng |
| ImageNet10Clustering | ImageClustering | image | eng |
| TinyImageNetClustering | ImageClustering | image | eng |
| BirdsnapZeroShot | ZeroShotClassification | image, text | eng |
| Caltech101ZeroShot | ZeroShotClassification | text, image | eng |
| CIFAR10ZeroShot | ZeroShotClassification | text, image | eng |
| CIFAR100ZeroShot | ZeroShotClassification | text, image | eng |
| CLEVRZeroShot | ZeroShotClassification | text, image | eng |
| CLEVRCountZeroShot | ZeroShotClassification | text, image | eng |
| Country211ZeroShot | ZeroShotClassification | image, text | eng |
| DTDZeroShot | ZeroShotClassification | image, text | eng |
| EuroSATZeroShot | ZeroShotClassification | image, text | eng |
| FER2013ZeroShot | ZeroShotClassification | image, text | eng |
| FGVCAircraftZeroShot | ZeroShotClassification | text, image | eng |
| Food101ZeroShot | ZeroShotClassification | text, image | eng |
| GTSRBZeroShot | ZeroShotClassification | image, text | eng |
| Imagenet1kZeroShot | ZeroShotClassification | image, text | eng |
| MNISTZeroShot | ZeroShotClassification | image, text | eng |
| OxfordPetsZeroShot | ZeroShotClassification | text, image | eng |
| PatchCamelyonZeroShot | ZeroShotClassification | image, text | eng |
| RenderedSST2 | ZeroShotClassification | text, image | eng |
| RESISC45ZeroShot | ZeroShotClassification | image, text | eng |
| StanfordCarsZeroShot | ZeroShotClassification | image, text | eng |
| STL10ZeroShot | ZeroShotClassification | image, text | eng |
| SUN397ZeroShot | ZeroShotClassification | image, text | eng |
| UCF101ZeroShot | ZeroShotClassification | image, text | eng |
| BLINKIT2IMultiChoice | VisionCentricQA | text, image | eng |
| BLINKIT2TMultiChoice | VisionCentricQA | text, image | eng |
| CVBenchCount | VisionCentricQA | image, text | eng |
| CVBenchRelation | VisionCentricQA | text, image | eng |
| CVBenchDepth | VisionCentricQA | text, image | eng |
| CVBenchDistance | VisionCentricQA | text, image | eng |
| AROCocoOrder | Compositionality | text, image | eng |
| AROFlickrOrder | Compositionality | text, image | eng |
| AROVisualAttribution | Compositionality | text, image | eng |
| AROVisualRelation | Compositionality | text, image | eng |
| SugarCrepe | Compositionality | text, image | eng |
| Winoground | Compositionality | text, image | eng |
| ImageCoDe | Compositionality | text, image | eng |
| STS12VisualSTS | VisualSTS(eng) | image | eng |
| STS13VisualSTS | VisualSTS(eng) | image | eng |
| STS14VisualSTS | VisualSTS(eng) | image | eng |
| STS15VisualSTS | VisualSTS(eng) | image | eng |
| STS16VisualSTS | VisualSTS(eng) | image | eng |
| BLINKIT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| BLINKIT2TRetrieval | Any2AnyRetrieval | text, image | eng |
| CIRRIT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| CUB200I2IRetrieval | Any2AnyRetrieval | image | eng |
| EDIST2ITRetrieval | Any2AnyRetrieval | text, image | eng |
| Fashion200kI2TRetrieval | Any2AnyRetrieval | text, image | eng |
| Fashion200kT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| FashionIQIT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| Flickr30kI2TRetrieval | Any2AnyRetrieval | text, image | eng |
| Flickr30kT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| FORBI2IRetrieval | Any2AnyRetrieval | image | eng |
| GLDv2I2IRetrieval | Any2AnyRetrieval | image | eng |
| GLDv2I2TRetrieval | Any2AnyRetrieval | text, image | eng |
| HatefulMemesI2TRetrieval | Any2AnyRetrieval | text, image | eng |
| HatefulMemesT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| ImageCoDeT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| InfoSeekIT2ITRetrieval | Any2AnyRetrieval | text, image | eng |
| InfoSeekIT2TRetrieval | Any2AnyRetrieval | text, image | eng |
| MemotionI2TRetrieval | Any2AnyRetrieval | text, image | eng |
| MemotionT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| METI2IRetrieval | Any2AnyRetrieval | image | eng |
| MSCOCOI2TRetrieval | Any2AnyRetrieval | text, image | eng |
| MSCOCOT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| NIGHTSI2IRetrieval | Any2AnyRetrieval | image | eng |
| OVENIT2ITRetrieval | Any2AnyRetrieval | image, text | eng |
| OVENIT2TRetrieval | Any2AnyRetrieval | text, image | eng |
| ROxfordEasyI2IRetrieval | Any2AnyRetrieval | image | eng |
| ROxfordMediumI2IRetrieval | Any2AnyRetrieval | image | eng |
| ROxfordHardI2IRetrieval | Any2AnyRetrieval | image | eng |
| RP2kI2IRetrieval | Any2AnyRetrieval | image | eng |
| RParisEasyI2IRetrieval | Any2AnyRetrieval | image | eng |
| RParisMediumI2IRetrieval | Any2AnyRetrieval | image | eng |
| RParisHardI2IRetrieval | Any2AnyRetrieval | image | eng |
| SciMMIRI2TRetrieval | Any2AnyRetrieval | text, image | eng |
| SciMMIRT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| SketchyI2IRetrieval | Any2AnyRetrieval | image | eng |
| SOPI2IRetrieval | Any2AnyRetrieval | image | eng |
| StanfordCarsI2IRetrieval | Any2AnyRetrieval | image | eng |
| TUBerlinT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| VidoreArxivQARetrieval | DocumentUnderstanding | text, image | eng |
| VidoreDocVQARetrieval | DocumentUnderstanding | text, image | eng |
| VidoreInfoVQARetrieval | DocumentUnderstanding | text, image | eng |
| VidoreTabfquadRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreTatdqaRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreShiftProjectRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreSyntheticDocQAAIRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreSyntheticDocQAEnergyRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreSyntheticDocQAGovernmentReportsRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreSyntheticDocQAHealthcareIndustryRetrieval | DocumentUnderstanding | text, image | eng |
| VisualNewsI2TRetrieval | Any2AnyRetrieval | image, text | eng |
| VisualNewsT2IRetrieval | Any2AnyRetrieval | image, text | eng |
| VizWizIT2TRetrieval | Any2AnyRetrieval | text, image | eng |
| VQA2IT2TRetrieval | Any2AnyRetrieval | text, image | eng |
| WebQAT2ITRetrieval | Any2AnyRetrieval | image, text | eng |
| WebQAT2TRetrieval | Any2AnyRetrieval | text | eng |
| VisualSTS17Eng | VisualSTS(eng) | image | ara, deu, eng, fra, ita, ... (9) |
| VisualSTS-b-Eng | VisualSTS(eng) | image | cmn, deu, eng, fra, ita, ... (10) |
Citation
@inproceedings{xiao2025mieb,
author = {Xiao, Chenghao and Chung, Isaac and Kerboua, Imene and Stirling, Jamie and Zhang, Xin and Kardos, M\'arton and Solomatin, Roman and Al Moubayed, Noura and Enevoldsen, Kenneth and Muennighoff, Niklas},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
pages = {22187-22198},
title = {MIEB: Massive Image Embedding Benchmark},
year = {2025},
}
MIEB(lite)¶
Multilingual image embedding quality across the same task types as MIEB(Multilingual), designed to be run at a fraction of the cost while maintaining relative model rankings.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| Country211 | ImageClassification | image | eng |
| DTD | ImageClassification | image | eng |
| EuroSAT | ImageClassification | image | eng |
| GTSRB | ImageClassification | image | eng |
| OxfordPets | ImageClassification | image | eng |
| PatchCamelyon | ImageClassification | image | eng |
| RESISC45 | ImageClassification | image | eng |
| SUN397 | ImageClassification | image | eng |
| ImageNetDog15Clustering | ImageClustering | image | eng |
| TinyImageNetClustering | ImageClustering | image | eng |
| CIFAR100ZeroShot | ZeroShotClassification | text, image | eng |
| Country211ZeroShot | ZeroShotClassification | image, text | eng |
| FER2013ZeroShot | ZeroShotClassification | image, text | eng |
| FGVCAircraftZeroShot | ZeroShotClassification | text, image | eng |
| Food101ZeroShot | ZeroShotClassification | text, image | eng |
| OxfordPetsZeroShot | ZeroShotClassification | text, image | eng |
| StanfordCarsZeroShot | ZeroShotClassification | image, text | eng |
| BLINKIT2IMultiChoice | VisionCentricQA | text, image | eng |
| CVBenchCount | VisionCentricQA | image, text | eng |
| CVBenchRelation | VisionCentricQA | text, image | eng |
| CVBenchDepth | VisionCentricQA | text, image | eng |
| CVBenchDistance | VisionCentricQA | text, image | eng |
| AROCocoOrder | Compositionality | text, image | eng |
| AROFlickrOrder | Compositionality | text, image | eng |
| AROVisualAttribution | Compositionality | text, image | eng |
| AROVisualRelation | Compositionality | text, image | eng |
| Winoground | Compositionality | text, image | eng |
| ImageCoDe | Compositionality | text, image | eng |
| STS13VisualSTS | VisualSTS(eng) | image | eng |
| STS15VisualSTS | VisualSTS(eng) | image | eng |
| VisualSTS17Multilingual | VisualSTS(multi) | image | ara, deu, eng, fra, ita, ... (9) |
| VisualSTS-b-Multilingual | VisualSTS(multi) | image | cmn, deu, eng, fra, ita, ... (10) |
| CIRRIT2IRetrieval | Any2AnyRetrieval | text, image | eng |
| CUB200I2IRetrieval | Any2AnyRetrieval | image | eng |
| Fashion200kI2TRetrieval | Any2AnyRetrieval | text, image | eng |
| HatefulMemesI2TRetrieval | Any2AnyRetrieval | text, image | eng |
| InfoSeekIT2TRetrieval | Any2AnyRetrieval | text, image | eng |
| NIGHTSI2IRetrieval | Any2AnyRetrieval | image | eng |
| OVENIT2TRetrieval | Any2AnyRetrieval | text, image | eng |
| RP2kI2IRetrieval | Any2AnyRetrieval | image | eng |
| VidoreDocVQARetrieval | DocumentUnderstanding | text, image | eng |
| VidoreInfoVQARetrieval | DocumentUnderstanding | text, image | eng |
| VidoreTabfquadRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreTatdqaRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreShiftProjectRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreSyntheticDocQAAIRetrieval | DocumentUnderstanding | text, image | eng |
| VisualNewsI2TRetrieval | Any2AnyRetrieval | image, text | eng |
| VQA2IT2TRetrieval | Any2AnyRetrieval | text, image | eng |
| WebQAT2ITRetrieval | Any2AnyRetrieval | image, text | eng |
| WITT2IRetrieval | Any2AnyMultilingualRetrieval | text, image | ara, bul, dan, ell, eng, ... (11) |
| XM3600T2IRetrieval | Any2AnyMultilingualRetrieval | text, image | ara, ben, ces, dan, deu, ... (38) |
Citation
@inproceedings{xiao2025mieb,
author = {Xiao, Chenghao and Chung, Isaac and Kerboua, Imene and Stirling, Jamie and Zhang, Xin and Kardos, M\'arton and Solomatin, Roman and Al Moubayed, Noura and Enevoldsen, Kenneth and Muennighoff, Niklas},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
pages = {22187-22198},
title = {MIEB: Massive Image Embedding Benchmark},
year = {2025},
}
MINERSBitextMining¶
Multilingual bitext mining quality across diverse language pairs, drawn from the MINERS benchmark for evaluating semantic retrieval in multilingual settings.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| BUCC | BitextMining | text | cmn, deu, eng, fra, rus |
| LinceMTBitextMining | BitextMining | text | eng, hin |
| NollySentiBitextMining | BitextMining | text | eng, hau, ibo, pcm, yor |
| NusaXBitextMining | BitextMining | text | ace, ban, bbc, bjn, bug, ... (12) |
| NusaTranslationBitextMining | BitextMining | text | abs, bbc, bew, bhp, ind, ... (12) |
| PhincBitextMining | BitextMining | text | eng, hin |
| Tatoeba | BitextMining | text | afr, amh, ang, ara, arq, ... (113) |
Citation
@inproceedings{winata2024miners,
address = {Miami, Florida, USA},
author = {Winata, Genta Indra and Zhang, Ruochen and Adelani, David Ifeoluwa},
booktitle = {Findings of the {A}ssociation for {C}omputational {L}inguistics: {EMNLP} 2024},
doi = {10.18653/v1/2024.findings-emnlp.155},
editor = {Al-Onaizan, Yaser and Bansal, Mohit and Chen, Yun-Nung},
month = {nov},
pages = {2742--2766},
publisher = {Association for Computational Linguistics},
title = {{MINERS}: Multilingual Language Models as Semantic Retrievers},
url = {https://aclanthology.org/2024.findings-emnlp.155/},
year = {2024},
}
MTEB(Africa, v1)¶
Text embedding quality across African languages spanning bitext mining, classification, clustering, pair classification, retrieval, reranking, and semantic similarity.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| SIB200Classification | Classification | text | ace, acm, acq, aeb, afr, ... (197) |
| FloresBitextMining | BitextMining | text | ace, acm, acq, aeb, afr, ... (196) |
| SIB200ClusteringS2S | Clustering | text | ace, acm, acq, aeb, afr, ... (197) |
| NTREXBitextMining | BitextMining | text | afr, amh, arb, aze, bak, ... (119) |
| AfriXNLI | PairClassification | text | amh, eng, ewe, fra, hau, ... (18) |
| EmotionAnalysisPlus | MultilabelClassification | text | afr, amh, arq, ary, cdo, ... (30) |
| AfriSentiClassification | Classification | text | amh, arq, ary, hau, ibo, ... (12) |
| MasakhaNEWSClassification | Classification | text | amh, eng, fra, hau, ibo, ... (16) |
| AfriHateClassification | Classification | text | amh, arq, ary, gaz, hau, ... (15) |
| KinNewsClassification | Classification | text | kin, run |
| InjongoIntent | Classification | text | amh, ewe, hau, ibo, kin, ... (16) |
| SIB200Classification.v2 | Classification | text | ace, acm, acq, aeb, afr, ... (197) |
| BelebeleRetrieval | Retrieval | text | acm, afr, als, amh, apc, ... (115) |
| MIRACLRetrievalHardNegatives | Retrieval | text | ara, ben, deu, eng, fas, ... (18) |
| MrTidyRetrieval | Retrieval | text | ara, ben, eng, fin, ind, ... (11) |
| XQuADRetrieval | Retrieval | text | arb, deu, ell, eng, hin, ... (12) |
| XM3600T2IRetrieval | Any2AnyMultilingualRetrieval | text, image | ara, ben, ces, dan, deu, ... (38) |
| AfriSentiLangClassification | Classification | text | amh, arq, ary, hau, ibo, ... (12) |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MassiveScenarioClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MultilingualSentimentClassification | Classification | text | ara, bam, bul, cmn, cym, ... (31) |
| NaijaSenti | Classification | text | hau, ibo, pcm, yor |
| SouthAfricanLangClassification | Classification | text | afr, eng, nbl, nso, sot, ... (11) |
| SiswatiNewsClassification | Classification | text | ssw |
| SwahiliNewsClassification | Classification | text | swa |
| TswanaNewsClassification | Classification | text | tsn |
| IsiZuluNewsClassification | Classification | text | zul |
| BibleNLPBitextMining | BitextMining | text | aai, aak, aau, aaz, abt, ... (829) |
| NollySentiBitextMining | BitextMining | text | eng, hau, ibo, pcm, yor |
| Tatoeba | BitextMining | text | afr, amh, ang, ara, arq, ... (113) |
| MasakhaNEWSClusteringP2P | Clustering | text | amh, eng, fra, hau, ibo, ... (16) |
| MasakhaNEWSClusteringS2S | Clustering | text | amh, eng, fra, hau, ibo, ... (16) |
| XNLI | PairClassification | text | ara, bul, deu, ell, eng, ... (14) |
| MIRACLReranking | Reranking | text | ara, ben, deu, eng, fas, ... (18) |
| SemRel24STS | STS | text | afr, amh, arb, arq, ary, ... (12) |
Citation
@article{enevoldsen2025mmtebmassivemultilingualtext,
author = {Kenneth Enevoldsen and Isaac Chung and Imene Kerboua and Márton Kardos and Ashwin Mathur and David Stap and Jay Gala and Wissam Siblini and Dominik Krzemiński and Genta Indra Winata and Saba Sturua and Saiteja Utpala and Mathieu Ciancone and Marion Schaeffer and Gabriel Sequeira and Diganta Misra and Shreeya Dhakal and Jonathan Rystrøm and Roman Solomatin and Ömer Çağatan and Akash Kundu and Martin Bernstorff and Shitao Xiao and Akshita Sukhlecha and Bhavish Pahwa and Rafał Poświata and Kranthi Kiran GV and Shawon Ashraf and Daniel Auras and Björn Plüster and Jan Philipp Harries and Loïc Magne and Isabelle Mohr and Mariya Hendriksen and Dawei Zhu and Hippolyte Gisserot-Boukhlef and Tom Aarsen and Jan Kostkan and Konrad Wojtasik and Taemin Lee and Marek Šuppa and Crystina Zhang and Roberta Rocca and Mohammed Hamdy and Andrianos Michail and John Yang and Manuel Faysse and Aleksei Vatolin and Nandan Thakur and Manan Dey and Dipam Vasani and Pranjal Chitale and Simone Tedeschi and Nguyen Tai and Artem Snegirev and Michael Günther and Mengzhou Xia and Weijia Shi and Xing Han Lù and Jordan Clive and Gayatri Krishnakumar and Anna Maksimova and Silvan Wehrli and Maria Tikhonova and Henil Panchal and Aleksandr Abramov and Malte Ostendorff and Zheng Liu and Simon Clematide and Lester James Miranda and Alena Fenogenova and Guangyu Song and Ruqiya Bin Safi and Wen-Ding Li and Alessia Borghini and Federico Cassano and Hongjin Su and Jimmy Lin and Howard Yen and Lasse Hansen and Sara Hooker and Chenghao Xiao and Vaibhav Adlakha and Orion Weller and Siva Reddy and Niklas Muennighoff},
doi = {10.48550/arXiv.2502.13595},
journal = {arXiv preprint arXiv:2502.13595},
publisher = {arXiv},
title = {MMTEB: Massive Multilingual Text Embedding Benchmark},
url = {https://arxiv.org/abs/2502.13595},
year = {2025},
}
MTEB(Africa, v1, lite)¶
Text embedding quality across 9 geographically diverse African languages, covering bitext mining, classification, clustering, pair classification, and retrieval. A computationally lighter subset of MTEB(Africa, v1) designed for faster evaluation.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| AfriHateClassification | Classification | text | amh, arq, ary, gaz, hau, ... (15) |
| AfriSentiClassification | Classification | text | amh, arq, ary, hau, ibo, ... (12) |
| MasakhaNEWSClassification | Classification | text | amh, eng, fra, hau, ibo, ... (16) |
| KinNewsClassification | Classification | text | kin, run |
| AfriXNLI | PairClassification | text | amh, eng, ewe, fra, hau, ... (18) |
| EmotionAnalysisPlus | MultilabelClassification | text | afr, amh, arq, ary, cdo, ... (30) |
| FloresBitextMining | BitextMining | text | ace, acm, acq, aeb, afr, ... (196) |
| InjongoIntent | Classification | text | amh, ewe, hau, ibo, kin, ... (16) |
| NTREXBitextMining | BitextMining | text | afr, amh, arb, aze, bak, ... (119) |
| SIB200Classification.v2 | Classification | text | ace, acm, acq, aeb, afr, ... (197) |
| SIB200Classification | Classification | text | ace, acm, acq, aeb, afr, ... (197) |
| SIB200ClusteringS2S | Clustering | text | ace, acm, acq, aeb, afr, ... (197) |
| BelebeleRetrieval | Retrieval | text | acm, afr, als, amh, apc, ... (115) |
Citation
@article{enevoldsen2025mmtebmassivemultilingualtext,
author = {Kenneth Enevoldsen and Isaac Chung and Imene Kerboua and Márton Kardos and Ashwin Mathur and David Stap and Jay Gala and Wissam Siblini and Dominik Krzemiński and Genta Indra Winata and Saba Sturua and Saiteja Utpala and Mathieu Ciancone and Marion Schaeffer and Gabriel Sequeira and Diganta Misra and Shreeya Dhakal and Jonathan Rystrøm and Roman Solomatin and Ömer Çağatan and Akash Kundu and Martin Bernstorff and Shitao Xiao and Akshita Sukhlecha and Bhavish Pahwa and Rafał Poświata and Kranthi Kiran GV and Shawon Ashraf and Daniel Auras and Björn Plüster and Jan Philipp Harries and Loïc Magne and Isabelle Mohr and Mariya Hendriksen and Dawei Zhu and Hippolyte Gisserot-Boukhlef and Tom Aarsen and Jan Kostkan and Konrad Wojtasik and Taemin Lee and Marek Šuppa and Crystina Zhang and Roberta Rocca and Mohammed Hamdy and Andrianos Michail and John Yang and Manuel Faysse and Aleksei Vatolin and Nandan Thakur and Manan Dey and Dipam Vasani and Pranjal Chitale and Simone Tedeschi and Nguyen Tai and Artem Snegirev and Michael Günther and Mengzhou Xia and Weijia Shi and Xing Han Lù and Jordan Clive and Gayatri Krishnakumar and Anna Maksimova and Silvan Wehrli and Maria Tikhonova and Henil Panchal and Aleksandr Abramov and Malte Ostendorff and Zheng Liu and Simon Clematide and Lester James Miranda and Alena Fenogenova and Guangyu Song and Ruqiya Bin Safi and Wen-Ding Li and Alessia Borghini and Federico Cassano and Hongjin Su and Jimmy Lin and Howard Yen and Lasse Hansen and Sara Hooker and Chenghao Xiao and Vaibhav Adlakha and Orion Weller and Siva Reddy and Niklas Muennighoff},
doi = {10.48550/arXiv.2502.13595},
journal = {arXiv preprint arXiv:2502.13595},
publisher = {arXiv},
title = {MMTEB: Massive Multilingual Text Embedding Benchmark},
url = {https://arxiv.org/abs/2502.13595},
year = {2025},
}
MTEB(Code, v1)¶
Code retrieval quality across a wide range of popular programming languages, covering code search, text-to-SQL, and code feedback tasks.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| AppsRetrieval | Retrieval | text | eng, python |
| CodeEditSearchRetrieval | Retrieval | text | c, c++, go, java, javascript, ... (13) |
| CodeFeedbackMT | Retrieval | text | eng |
| CodeFeedbackST | Retrieval | text | eng |
| CodeSearchNetCCRetrieval | Retrieval | text | go, java, javascript, php, python, ... (6) |
| CodeSearchNetRetrieval | Retrieval | text | go, java, javascript, php, python, ... (6) |
| CodeTransOceanContest | Retrieval | text | c++, python |
| CodeTransOceanDL | Retrieval | text | python |
| CosQA | Retrieval | text | eng, python |
| COIRCodeSearchNetRetrieval | Retrieval | text | go, java, javascript, php, python, ... (6) |
| StackOverflowQA | Retrieval | text | eng |
| SyntheticText2SQL | Retrieval | text | eng, sql |
Citation
@article{enevoldsen2025mmtebmassivemultilingualtext,
author = {Kenneth Enevoldsen and Isaac Chung and Imene Kerboua and Márton Kardos and Ashwin Mathur and David Stap and Jay Gala and Wissam Siblini and Dominik Krzemiński and Genta Indra Winata and Saba Sturua and Saiteja Utpala and Mathieu Ciancone and Marion Schaeffer and Gabriel Sequeira and Diganta Misra and Shreeya Dhakal and Jonathan Rystrøm and Roman Solomatin and Ömer Çağatan and Akash Kundu and Martin Bernstorff and Shitao Xiao and Akshita Sukhlecha and Bhavish Pahwa and Rafał Poświata and Kranthi Kiran GV and Shawon Ashraf and Daniel Auras and Björn Plüster and Jan Philipp Harries and Loïc Magne and Isabelle Mohr and Mariya Hendriksen and Dawei Zhu and Hippolyte Gisserot-Boukhlef and Tom Aarsen and Jan Kostkan and Konrad Wojtasik and Taemin Lee and Marek Šuppa and Crystina Zhang and Roberta Rocca and Mohammed Hamdy and Andrianos Michail and John Yang and Manuel Faysse and Aleksei Vatolin and Nandan Thakur and Manan Dey and Dipam Vasani and Pranjal Chitale and Simone Tedeschi and Nguyen Tai and Artem Snegirev and Michael Günther and Mengzhou Xia and Weijia Shi and Xing Han Lù and Jordan Clive and Gayatri Krishnakumar and Anna Maksimova and Silvan Wehrli and Maria Tikhonova and Henil Panchal and Aleksandr Abramov and Malte Ostendorff and Zheng Liu and Simon Clematide and Lester James Miranda and Alena Fenogenova and Guangyu Song and Ruqiya Bin Safi and Wen-Ding Li and Alessia Borghini and Federico Cassano and Hongjin Su and Jimmy Lin and Howard Yen and Lasse Hansen and Sara Hooker and Chenghao Xiao and Vaibhav Adlakha and Orion Weller and Siva Reddy and Niklas Muennighoff},
doi = {10.48550/arXiv.2502.13595},
journal = {arXiv preprint arXiv:2502.13595},
publisher = {arXiv},
title = {MMTEB: Massive Multilingual Text Embedding Benchmark},
url = {https://arxiv.org/abs/2502.13595},
year = {2025},
}
MTEB(Europe, v1)¶
Text embedding quality across European languages spanning bitext mining, classification, clustering, pair classification, retrieval, reranking, and semantic similarity.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| BornholmBitextMining | BitextMining | text | dan |
| BibleNLPBitextMining | BitextMining | text | aai, aak, aau, aaz, abt, ... (829) |
| BUCC.v2 | BitextMining | text | cmn, deu, eng, fra, rus |
| DiaBlaBitextMining | BitextMining | text | eng, fra |
| FloresBitextMining | BitextMining | text | ace, acm, acq, aeb, afr, ... (196) |
| NorwegianCourtsBitextMining | BitextMining | text | nno, nob |
| NTREXBitextMining | BitextMining | text | afr, amh, arb, aze, bak, ... (119) |
| BulgarianStoreReviewSentimentClassfication | Classification | text | bul |
| CzechProductReviewSentimentClassification | Classification | text | ces |
| GreekLegalCodeClassification | Classification | text | ell |
| DBpediaClassification | Classification | text | eng |
| FinancialPhrasebankClassification | Classification | text | eng |
| PoemSentimentClassification | Classification | text | eng |
| ToxicChatClassification | Classification | text | eng |
| ToxicConversationsClassification | Classification | text | eng |
| EstonianValenceClassification | Classification | text | est |
| ItaCaseholdClassification | Classification | text | ita |
| AmazonCounterfactualClassification | Classification | text | deu, eng, jpn |
| MassiveScenarioClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MultiHateClassification | Classification | text | ara, cmn, deu, eng, fra, ... (11) |
| ScalaClassification | Classification | text | dan, nno, nob, swe |
| SwissJudgementClassification | Classification | text | deu, fra, ita |
| TweetSentimentClassification | Classification | text | ara, deu, eng, fra, hin, ... (8) |
| CBD | Classification | text | pol |
| PolEmo2.0-OUT | Classification | text | pol |
| CSFDSKMovieReviewSentimentClassification | Classification | text | slk |
| DalajClassification | Classification | text | swe |
| WikiCitiesClustering | Clustering | text | eng |
| RomaniBibleClustering | Clustering | text | rom |
| BigPatentClustering.v2 | Clustering | text | eng |
| BiorxivClusteringP2P.v2 | Clustering | text | eng |
| AlloProfClusteringS2S.v2 | Clustering | text | fra |
| HALClusteringS2S.v2 | Clustering | text | fra |
| SIB200ClusteringS2S | Clustering | text | ace, acm, acq, aeb, afr, ... (197) |
| WikiClusteringP2P.v2 | Clustering | text | bos, cat, ces, dan, eus, ... (14) |
| StackOverflowQA | Retrieval | text | eng |
| TwitterHjerneRetrieval | Retrieval | text | dan |
| LegalQuAD | Retrieval | text | deu |
| ArguAna | Retrieval | text | eng |
| HagridRetrieval | Retrieval | text | eng |
| LegalBenchCorporateLobbying | Retrieval | text | eng |
| LEMBPasskeyRetrieval | Retrieval | text | eng |
| SCIDOCS | Retrieval | text | eng |
| SpartQA | Retrieval | text | eng |
| TempReasonL1 | Retrieval | text | eng |
| WinoGrande | Retrieval | text | eng |
| AlloprofRetrieval | Retrieval | text | fra |
| BelebeleRetrieval | Retrieval | text | acm, afr, als, amh, apc, ... (115) |
| StatcanDialogueDatasetRetrieval | Retrieval | text | eng, fra |
| WikipediaRetrievalMultilingual | Retrieval | text | ben, bul, ces, dan, deu, ... (16) |
| Core17InstructionRetrieval | InstructionReranking | text | eng |
| News21InstructionRetrieval | InstructionReranking | text | eng |
| Robust04InstructionRetrieval | InstructionReranking | text | eng |
| MalteseNewsClassification | MultilabelClassification | text | mlt |
| MultiEURLEXMultilabelClassification | MultilabelClassification | text | bul, ces, dan, deu, ell, ... (23) |
| CTKFactsNLI | PairClassification | text | ces |
| SprintDuplicateQuestions | PairClassification | text | eng |
| OpusparcusPC | PairClassification | text | deu, eng, fin, fra, rus, ... (6) |
| RTE3 | PairClassification | text | deu, eng, fra, ita |
| XNLI | PairClassification | text | ara, bul, deu, ell, eng, ... (14) |
| PSC | PairClassification | text | pol |
| WebLINXCandidatesReranking | Reranking | text | eng |
| AlloprofReranking | Reranking | text | fra |
| WikipediaRerankingMultilingual | Reranking | text | ben, bul, ces, dan, deu, ... (18) |
| SICK-R | STS | text | eng |
| STS12 | STS | text | eng |
| STS14 | STS | text | eng |
| STS15 | STS | text | eng |
| STSBenchmark | STS | text | eng |
| FinParaSTS | STS | text | fin |
| STS17 | STS | text | ara, deu, eng, fra, ita, ... (9) |
| SICK-R-PL | STS | text | pol |
| STSES | STS | text | spa |
Citation
@article{enevoldsen2025mmtebmassivemultilingualtext,
author = {Kenneth Enevoldsen and Isaac Chung and Imene Kerboua and Márton Kardos and Ashwin Mathur and David Stap and Jay Gala and Wissam Siblini and Dominik Krzemiński and Genta Indra Winata and Saba Sturua and Saiteja Utpala and Mathieu Ciancone and Marion Schaeffer and Gabriel Sequeira and Diganta Misra and Shreeya Dhakal and Jonathan Rystrøm and Roman Solomatin and Ömer Çağatan and Akash Kundu and Martin Bernstorff and Shitao Xiao and Akshita Sukhlecha and Bhavish Pahwa and Rafał Poświata and Kranthi Kiran GV and Shawon Ashraf and Daniel Auras and Björn Plüster and Jan Philipp Harries and Loïc Magne and Isabelle Mohr and Mariya Hendriksen and Dawei Zhu and Hippolyte Gisserot-Boukhlef and Tom Aarsen and Jan Kostkan and Konrad Wojtasik and Taemin Lee and Marek Šuppa and Crystina Zhang and Roberta Rocca and Mohammed Hamdy and Andrianos Michail and John Yang and Manuel Faysse and Aleksei Vatolin and Nandan Thakur and Manan Dey and Dipam Vasani and Pranjal Chitale and Simone Tedeschi and Nguyen Tai and Artem Snegirev and Michael Günther and Mengzhou Xia and Weijia Shi and Xing Han Lù and Jordan Clive and Gayatri Krishnakumar and Anna Maksimova and Silvan Wehrli and Maria Tikhonova and Henil Panchal and Aleksandr Abramov and Malte Ostendorff and Zheng Liu and Simon Clematide and Lester James Miranda and Alena Fenogenova and Guangyu Song and Ruqiya Bin Safi and Wen-Ding Li and Alessia Borghini and Federico Cassano and Hongjin Su and Jimmy Lin and Howard Yen and Lasse Hansen and Sara Hooker and Chenghao Xiao and Vaibhav Adlakha and Orion Weller and Siva Reddy and Niklas Muennighoff},
doi = {10.48550/arXiv.2502.13595},
journal = {arXiv preprint arXiv:2502.13595},
publisher = {arXiv},
title = {MMTEB: Massive Multilingual Text Embedding Benchmark},
url = {https://arxiv.org/abs/2502.13595},
year = {2025},
}
MTEB(Indic, v1)¶
Text embedding quality across Indic languages spanning bitext mining, classification, clustering, pair classification, retrieval, reranking, and semantic similarity.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| IN22ConvBitextMining | BitextMining | text | asm, ben, brx, doi, eng, ... (23) |
| IN22GenBitextMining | BitextMining | text | asm, ben, brx, doi, eng, ... (23) |
| SIB200ClusteringS2S | Clustering | text | ace, acm, acq, aeb, afr, ... (197) |
| BengaliSentimentAnalysis | Classification | text | ben |
| GujaratiNewsClassification | Classification | text | guj |
| HindiDiscourseClassification | Classification | text | hin |
| SentimentAnalysisHindi | Classification | text | hin |
| MalayalamNewsClassification | Classification | text | mal |
| MTOPIntentClassification | Classification | text | deu, eng, fra, hin, spa, ... (6) |
| MultiHateClassification | Classification | text | ara, cmn, deu, eng, fra, ... (11) |
| TweetSentimentClassification | Classification | text | ara, deu, eng, fra, hin, ... (8) |
| NepaliNewsClassification | Classification | text | nep |
| PunjabiNewsClassification | Classification | text | pan |
| SanskritShlokasClassification | Classification | text | san |
| UrduRomanSentimentClassification | Classification | text | urd |
| XNLI | PairClassification | text | ara, bul, deu, ell, eng, ... (14) |
| BelebeleRetrieval | Retrieval | text | acm, afr, als, amh, apc, ... (115) |
| XQuADRetrieval | Retrieval | text | arb, deu, ell, eng, hin, ... (12) |
| WikipediaRerankingMultilingual | Reranking | text | ben, bul, ces, dan, deu, ... (18) |
| IndicCrosslingualSTS | STS | text | asm, ben, eng, guj, hin, ... (13) |
Citation
@article{enevoldsen2025mmtebmassivemultilingualtext,
author = {Kenneth Enevoldsen and Isaac Chung and Imene Kerboua and Márton Kardos and Ashwin Mathur and David Stap and Jay Gala and Wissam Siblini and Dominik Krzemiński and Genta Indra Winata and Saba Sturua and Saiteja Utpala and Mathieu Ciancone and Marion Schaeffer and Gabriel Sequeira and Diganta Misra and Shreeya Dhakal and Jonathan Rystrøm and Roman Solomatin and Ömer Çağatan and Akash Kundu and Martin Bernstorff and Shitao Xiao and Akshita Sukhlecha and Bhavish Pahwa and Rafał Poświata and Kranthi Kiran GV and Shawon Ashraf and Daniel Auras and Björn Plüster and Jan Philipp Harries and Loïc Magne and Isabelle Mohr and Mariya Hendriksen and Dawei Zhu and Hippolyte Gisserot-Boukhlef and Tom Aarsen and Jan Kostkan and Konrad Wojtasik and Taemin Lee and Marek Šuppa and Crystina Zhang and Roberta Rocca and Mohammed Hamdy and Andrianos Michail and John Yang and Manuel Faysse and Aleksei Vatolin and Nandan Thakur and Manan Dey and Dipam Vasani and Pranjal Chitale and Simone Tedeschi and Nguyen Tai and Artem Snegirev and Michael Günther and Mengzhou Xia and Weijia Shi and Xing Han Lù and Jordan Clive and Gayatri Krishnakumar and Anna Maksimova and Silvan Wehrli and Maria Tikhonova and Henil Panchal and Aleksandr Abramov and Malte Ostendorff and Zheng Liu and Simon Clematide and Lester James Miranda and Alena Fenogenova and Guangyu Song and Ruqiya Bin Safi and Wen-Ding Li and Alessia Borghini and Federico Cassano and Hongjin Su and Jimmy Lin and Howard Yen and Lasse Hansen and Sara Hooker and Chenghao Xiao and Vaibhav Adlakha and Orion Weller and Siva Reddy and Niklas Muennighoff},
doi = {10.48550/arXiv.2502.13595},
journal = {arXiv preprint arXiv:2502.13595},
publisher = {arXiv},
title = {MMTEB: Massive Multilingual Text Embedding Benchmark},
url = {https://arxiv.org/abs/2502.13595},
year = {2025},
}
MTEB(Law, v1)¶
Legal document retrieval across case documents, statutes, legal Q&A, and legal summarization in multiple languages.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| AILACasedocs | Retrieval | text | eng |
| AILAStatutes | Retrieval | text | eng |
| LegalSummarization | Retrieval | text | eng |
| GerDaLIRSmall | Retrieval | text | deu |
| LeCaRDv2 | Retrieval | text | zho |
| LegalBenchConsumerContractsQA | Retrieval | text | eng |
| LegalBenchCorporateLobbying | Retrieval | text | eng |
| LegalQuAD | Retrieval | text | deu |
MTEB(Medical, v1)¶
Medical information retrieval across clinical, biomedical, and consumer health domains, spanning retrieval, reranking, and clustering tasks.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| CUREv1 | Retrieval | text | eng, fra, spa |
| NFCorpus | Retrieval | text | eng |
| TRECCOVID | Retrieval | text | eng |
| TRECCOVID-PL | Retrieval | text | pol |
| SciFact | Retrieval | text | eng |
| SciFact-PL | Retrieval | text | pol |
| MedicalQARetrieval | Retrieval | text | eng |
| PublicHealthQA | Retrieval | text | ara, eng, fra, kor, rus, ... (8) |
| MedrxivClusteringP2P.v2 | Clustering | text | eng |
| MedrxivClusteringS2S.v2 | Clustering | text | eng |
| CmedqaRetrieval | Retrieval | text | cmn |
| CMedQAv2-reranking | Reranking | text | cmn |
MTEB(Multilingual, v1)¶
Multilingual text embedding quality across 250+ languages spanning bitext mining, classification, clustering, retrieval, reranking, and semantic similarity. Superseded by MTEB(Multilingual, v2) after SNLHierarchicalClustering was removed from Hugging Face Hub.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| BornholmBitextMining | BitextMining | text | dan |
| BibleNLPBitextMining | BitextMining | text | aai, aak, aau, aaz, abt, ... (829) |
| BUCC.v2 | BitextMining | text | cmn, deu, eng, fra, rus |
| DiaBlaBitextMining | BitextMining | text | eng, fra |
| FloresBitextMining | BitextMining | text | ace, acm, acq, aeb, afr, ... (196) |
| IN22GenBitextMining | BitextMining | text | asm, ben, brx, doi, eng, ... (23) |
| IndicGenBenchFloresBitextMining | BitextMining | text | asm, awa, ben, bgc, bho, ... (30) |
| NollySentiBitextMining | BitextMining | text | eng, hau, ibo, pcm, yor |
| NorwegianCourtsBitextMining | BitextMining | text | nno, nob |
| NTREXBitextMining | BitextMining | text | afr, amh, arb, aze, bak, ... (119) |
| NusaTranslationBitextMining | BitextMining | text | abs, bbc, bew, bhp, ind, ... (12) |
| NusaXBitextMining | BitextMining | text | ace, ban, bbc, bjn, bug, ... (12) |
| Tatoeba | BitextMining | text | afr, amh, ang, ara, arq, ... (113) |
| BulgarianStoreReviewSentimentClassfication | Classification | text | bul |
| CzechProductReviewSentimentClassification | Classification | text | ces |
| GreekLegalCodeClassification | Classification | text | ell |
| DBpediaClassification | Classification | text | eng |
| FinancialPhrasebankClassification | Classification | text | eng |
| PoemSentimentClassification | Classification | text | eng |
| ToxicConversationsClassification | Classification | text | eng |
| TweetTopicSingleClassification | Classification | text | eng |
| EstonianValenceClassification | Classification | text | est |
| FilipinoShopeeReviewsClassification | Classification | text | fil |
| GujaratiNewsClassification | Classification | text | guj |
| SentimentAnalysisHindi | Classification | text | hin |
| IndonesianIdClickbaitClassification | Classification | text | ind |
| ItaCaseholdClassification | Classification | text | ita |
| KorSarcasmClassification | Classification | text | kor |
| KurdishSentimentClassification | Classification | text | kur |
| MacedonianTweetSentimentClassification | Classification | text | mkd |
| AfriSentiClassification | Classification | text | amh, arq, ary, hau, ibo, ... (12) |
| AmazonCounterfactualClassification | Classification | text | deu, eng, jpn |
| CataloniaTweetClassification | Classification | text | cat, spa |
| CyrillicTurkicLangClassification | Classification | text | bak, chv, kaz, kir, krc, ... (9) |
| IndicLangClassification | Classification | text | asm, ben, brx, doi, gom, ... (22) |
| MasakhaNEWSClassification | Classification | text | amh, eng, fra, hau, ibo, ... (16) |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MultiHateClassification | Classification | text | ara, cmn, deu, eng, fra, ... (11) |
| NordicLangClassification | Classification | text | dan, fao, isl, nno, nob, ... (6) |
| NusaParagraphEmotionClassification | Classification | text | bbc, bew, bug, jav, mad, ... (10) |
| NusaX-senti | Classification | text | ace, ban, bbc, bjn, bug, ... (12) |
| ScalaClassification | Classification | text | dan, nno, nob, swe |
| SwissJudgementClassification | Classification | text | deu, fra, ita |
| NepaliNewsClassification | Classification | text | nep |
| OdiaNewsClassification | Classification | text | ory |
| PunjabiNewsClassification | Classification | text | pan |
| PolEmo2.0-OUT | Classification | text | pol |
| PAC | Classification | text | pol |
| SinhalaNewsClassification | Classification | text | sin |
| CSFDSKMovieReviewSentimentClassification | Classification | text | slk |
| SiswatiNewsClassification | Classification | text | ssw |
| SlovakMovieReviewSentimentClassification | Classification | text | slk |
| SwahiliNewsClassification | Classification | text | swa |
| DalajClassification | Classification | text | swe |
| TswanaNewsClassification | Classification | text | tsn |
| IsiZuluNewsClassification | Classification | text | zul |
| WikiCitiesClustering | Clustering | text | eng |
| MasakhaNEWSClusteringS2S | Clustering | text | amh, eng, fra, hau, ibo, ... (16) |
| RomaniBibleClustering | Clustering | text | rom |
| ArXivHierarchicalClusteringP2P | Clustering | text | eng |
| ArXivHierarchicalClusteringS2S | Clustering | text | eng |
| BigPatentClustering.v2 | Clustering | text | eng |
| BiorxivClusteringP2P.v2 | Clustering | text | eng |
| MedrxivClusteringP2P.v2 | Clustering | text | eng |
| StackExchangeClustering.v2 | Clustering | text | eng |
| AlloProfClusteringS2S.v2 | Clustering | text | fra |
| HALClusteringS2S.v2 | Clustering | text | fra |
| SIB200ClusteringS2S | Clustering | text | ace, acm, acq, aeb, afr, ... (197) |
| WikiClusteringP2P.v2 | Clustering | text | bos, cat, ces, dan, eus, ... (14) |
| PlscClusteringP2P.v2 | Clustering | text | pol |
| SwednClusteringP2P | Clustering | text | swe |
| CLSClusteringP2P.v2 | Clustering | text | cmn |
| StackOverflowQA | Retrieval | text | eng |
| TwitterHjerneRetrieval | Retrieval | text | dan |
| AILAStatutes | Retrieval | text | eng |
| ArguAna | Retrieval | text | eng |
| HagridRetrieval | Retrieval | text | eng |
| LegalBenchCorporateLobbying | Retrieval | text | eng |
| LEMBPasskeyRetrieval | Retrieval | text | eng |
| SCIDOCS | Retrieval | text | eng |
| SpartQA | Retrieval | text | eng |
| TempReasonL1 | Retrieval | text | eng |
| TRECCOVID | Retrieval | text | eng |
| WinoGrande | Retrieval | text | eng |
| BelebeleRetrieval | Retrieval | text | acm, afr, als, amh, apc, ... (115) |
| MLQARetrieval | Retrieval | text | ara, deu, eng, hin, spa, ... (7) |
| StatcanDialogueDatasetRetrieval | Retrieval | text | eng, fra |
| WikipediaRetrievalMultilingual | Retrieval | text | ben, bul, ces, dan, deu, ... (16) |
| CovidRetrieval | Retrieval | text | cmn |
| Core17InstructionRetrieval | InstructionReranking | text | eng |
| News21InstructionRetrieval | InstructionReranking | text | eng |
| Robust04InstructionRetrieval | InstructionReranking | text | eng |
| KorHateSpeechMLClassification | MultilabelClassification | text | kor |
| MalteseNewsClassification | MultilabelClassification | text | mlt |
| MultiEURLEXMultilabelClassification | MultilabelClassification | text | bul, ces, dan, deu, ell, ... (23) |
| BrazilianToxicTweetsClassification | MultilabelClassification | text | por |
| CEDRClassification | MultilabelClassification | text | rus |
| CTKFactsNLI | PairClassification | text | ces |
| SprintDuplicateQuestions | PairClassification | text | eng |
| TwitterURLCorpus | PairClassification | text | eng |
| ArmenianParaphrasePC | PairClassification | text | hye |
| indonli | PairClassification | text | ind |
| OpusparcusPC | PairClassification | text | deu, eng, fin, fra, rus, ... (6) |
| PawsXPairClassification | PairClassification | text | cmn, deu, eng, fra, jpn, ... (7) |
| RTE3 | PairClassification | text | deu, eng, fra, ita |
| XNLI | PairClassification | text | ara, bul, deu, ell, eng, ... (14) |
| PpcPC | PairClassification | text | pol |
| TERRa | PairClassification | text | rus |
| WebLINXCandidatesReranking | Reranking | text | eng |
| AlloprofReranking | Reranking | text | fra |
| VoyageMMarcoReranking | Reranking | text | jpn |
| WikipediaRerankingMultilingual | Reranking | text | ben, bul, ces, dan, deu, ... (18) |
| RuBQReranking | Reranking | text | rus |
| T2Reranking | Reranking | text | cmn |
| GermanSTSBenchmark | STS | text | deu |
| SICK-R | STS | text | eng |
| STS12 | STS | text | eng |
| STS13 | STS | text | eng |
| STS14 | STS | text | eng |
| STS15 | STS | text | eng |
| STSBenchmark | STS | text | eng |
| FaroeseSTS | STS | text | fao |
| FinParaSTS | STS | text | fin |
| JSICK | STS | text | jpn |
| IndicCrosslingualSTS | STS | text | asm, ben, eng, guj, hin, ... (13) |
| SemRel24STS | STS | text | afr, amh, arb, arq, ary, ... (12) |
| STS17 | STS | text | ara, deu, eng, fra, ita, ... (9) |
| STS22.v2 | STS | text | ara, cmn, deu, eng, fra, ... (10) |
| STSES | STS | text | spa |
| STSB | STS | text | cmn |
| MIRACLRetrievalHardNegatives | Retrieval | text | ara, ben, deu, eng, fas, ... (18) |
| SNLHierarchicalClusteringP2P | Clustering | text | nob |
Citation
@article{enevoldsen2025mmtebmassivemultilingualtext,
author = {Kenneth Enevoldsen and Isaac Chung and Imene Kerboua and Márton Kardos and Ashwin Mathur and David Stap and Jay Gala and Wissam Siblini and Dominik Krzemiński and Genta Indra Winata and Saba Sturua and Saiteja Utpala and Mathieu Ciancone and Marion Schaeffer and Gabriel Sequeira and Diganta Misra and Shreeya Dhakal and Jonathan Rystrøm and Roman Solomatin and Ömer Çağatan and Akash Kundu and Martin Bernstorff and Shitao Xiao and Akshita Sukhlecha and Bhavish Pahwa and Rafał Poświata and Kranthi Kiran GV and Shawon Ashraf and Daniel Auras and Björn Plüster and Jan Philipp Harries and Loïc Magne and Isabelle Mohr and Mariya Hendriksen and Dawei Zhu and Hippolyte Gisserot-Boukhlef and Tom Aarsen and Jan Kostkan and Konrad Wojtasik and Taemin Lee and Marek Šuppa and Crystina Zhang and Roberta Rocca and Mohammed Hamdy and Andrianos Michail and John Yang and Manuel Faysse and Aleksei Vatolin and Nandan Thakur and Manan Dey and Dipam Vasani and Pranjal Chitale and Simone Tedeschi and Nguyen Tai and Artem Snegirev and Michael Günther and Mengzhou Xia and Weijia Shi and Xing Han Lù and Jordan Clive and Gayatri Krishnakumar and Anna Maksimova and Silvan Wehrli and Maria Tikhonova and Henil Panchal and Aleksandr Abramov and Malte Ostendorff and Zheng Liu and Simon Clematide and Lester James Miranda and Alena Fenogenova and Guangyu Song and Ruqiya Bin Safi and Wen-Ding Li and Alessia Borghini and Federico Cassano and Hongjin Su and Jimmy Lin and Howard Yen and Lasse Hansen and Sara Hooker and Chenghao Xiao and Vaibhav Adlakha and Orion Weller and Siva Reddy and Niklas Muennighoff},
doi = {10.48550/arXiv.2502.13595},
journal = {arXiv preprint arXiv:2502.13595},
publisher = {arXiv},
title = {MMTEB: Massive Multilingual Text Embedding Benchmark},
url = {https://arxiv.org/abs/2502.13595},
year = {2025},
}
MTEB(Multilingual, v2)¶
MMTEB measures multilingual text embedding quality across 250+ languages spanning classification, clustering, retrieval semantic similarity and more, driven by curated community contributions.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| BornholmBitextMining | BitextMining | text | dan |
| BibleNLPBitextMining | BitextMining | text | aai, aak, aau, aaz, abt, ... (829) |
| BUCC.v2 | BitextMining | text | cmn, deu, eng, fra, rus |
| DiaBlaBitextMining | BitextMining | text | eng, fra |
| FloresBitextMining | BitextMining | text | ace, acm, acq, aeb, afr, ... (196) |
| IN22GenBitextMining | BitextMining | text | asm, ben, brx, doi, eng, ... (23) |
| IndicGenBenchFloresBitextMining | BitextMining | text | asm, awa, ben, bgc, bho, ... (30) |
| NollySentiBitextMining | BitextMining | text | eng, hau, ibo, pcm, yor |
| NorwegianCourtsBitextMining | BitextMining | text | nno, nob |
| NTREXBitextMining | BitextMining | text | afr, amh, arb, aze, bak, ... (119) |
| NusaTranslationBitextMining | BitextMining | text | abs, bbc, bew, bhp, ind, ... (12) |
| NusaXBitextMining | BitextMining | text | ace, ban, bbc, bjn, bug, ... (12) |
| Tatoeba | BitextMining | text | afr, amh, ang, ara, arq, ... (113) |
| BulgarianStoreReviewSentimentClassfication | Classification | text | bul |
| CzechProductReviewSentimentClassification | Classification | text | ces |
| GreekLegalCodeClassification | Classification | text | ell |
| DBpediaClassification | Classification | text | eng |
| FinancialPhrasebankClassification | Classification | text | eng |
| PoemSentimentClassification | Classification | text | eng |
| ToxicConversationsClassification | Classification | text | eng |
| TweetTopicSingleClassification | Classification | text | eng |
| EstonianValenceClassification | Classification | text | est |
| FilipinoShopeeReviewsClassification | Classification | text | fil |
| GujaratiNewsClassification | Classification | text | guj |
| SentimentAnalysisHindi | Classification | text | hin |
| IndonesianIdClickbaitClassification | Classification | text | ind |
| ItaCaseholdClassification | Classification | text | ita |
| KorSarcasmClassification | Classification | text | kor |
| KurdishSentimentClassification | Classification | text | kur |
| MacedonianTweetSentimentClassification | Classification | text | mkd |
| AfriSentiClassification | Classification | text | amh, arq, ary, hau, ibo, ... (12) |
| AmazonCounterfactualClassification | Classification | text | deu, eng, jpn |
| CataloniaTweetClassification | Classification | text | cat, spa |
| CyrillicTurkicLangClassification | Classification | text | bak, chv, kaz, kir, krc, ... (9) |
| IndicLangClassification | Classification | text | asm, ben, brx, doi, gom, ... (22) |
| MasakhaNEWSClassification | Classification | text | amh, eng, fra, hau, ibo, ... (16) |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MultiHateClassification | Classification | text | ara, cmn, deu, eng, fra, ... (11) |
| NordicLangClassification | Classification | text | dan, fao, isl, nno, nob, ... (6) |
| NusaParagraphEmotionClassification | Classification | text | bbc, bew, bug, jav, mad, ... (10) |
| NusaX-senti | Classification | text | ace, ban, bbc, bjn, bug, ... (12) |
| ScalaClassification | Classification | text | dan, nno, nob, swe |
| SwissJudgementClassification | Classification | text | deu, fra, ita |
| NepaliNewsClassification | Classification | text | nep |
| OdiaNewsClassification | Classification | text | ory |
| PunjabiNewsClassification | Classification | text | pan |
| PolEmo2.0-OUT | Classification | text | pol |
| PAC | Classification | text | pol |
| SinhalaNewsClassification | Classification | text | sin |
| CSFDSKMovieReviewSentimentClassification | Classification | text | slk |
| SiswatiNewsClassification | Classification | text | ssw |
| SlovakMovieReviewSentimentClassification | Classification | text | slk |
| SwahiliNewsClassification | Classification | text | swa |
| DalajClassification | Classification | text | swe |
| TswanaNewsClassification | Classification | text | tsn |
| IsiZuluNewsClassification | Classification | text | zul |
| WikiCitiesClustering | Clustering | text | eng |
| MasakhaNEWSClusteringS2S | Clustering | text | amh, eng, fra, hau, ibo, ... (16) |
| RomaniBibleClustering | Clustering | text | rom |
| ArXivHierarchicalClusteringP2P | Clustering | text | eng |
| ArXivHierarchicalClusteringS2S | Clustering | text | eng |
| BigPatentClustering.v2 | Clustering | text | eng |
| BiorxivClusteringP2P.v2 | Clustering | text | eng |
| MedrxivClusteringP2P.v2 | Clustering | text | eng |
| StackExchangeClustering.v2 | Clustering | text | eng |
| AlloProfClusteringS2S.v2 | Clustering | text | fra |
| HALClusteringS2S.v2 | Clustering | text | fra |
| SIB200ClusteringS2S | Clustering | text | ace, acm, acq, aeb, afr, ... (197) |
| WikiClusteringP2P.v2 | Clustering | text | bos, cat, ces, dan, eus, ... (14) |
| PlscClusteringP2P.v2 | Clustering | text | pol |
| SwednClusteringP2P | Clustering | text | swe |
| CLSClusteringP2P.v2 | Clustering | text | cmn |
| StackOverflowQA | Retrieval | text | eng |
| TwitterHjerneRetrieval | Retrieval | text | dan |
| AILAStatutes | Retrieval | text | eng |
| ArguAna | Retrieval | text | eng |
| HagridRetrieval | Retrieval | text | eng |
| LegalBenchCorporateLobbying | Retrieval | text | eng |
| LEMBPasskeyRetrieval | Retrieval | text | eng |
| SCIDOCS | Retrieval | text | eng |
| SpartQA | Retrieval | text | eng |
| TempReasonL1 | Retrieval | text | eng |
| TRECCOVID | Retrieval | text | eng |
| WinoGrande | Retrieval | text | eng |
| BelebeleRetrieval | Retrieval | text | acm, afr, als, amh, apc, ... (115) |
| MLQARetrieval | Retrieval | text | ara, deu, eng, hin, spa, ... (7) |
| StatcanDialogueDatasetRetrieval | Retrieval | text | eng, fra |
| WikipediaRetrievalMultilingual | Retrieval | text | ben, bul, ces, dan, deu, ... (16) |
| CovidRetrieval | Retrieval | text | cmn |
| Core17InstructionRetrieval | InstructionReranking | text | eng |
| News21InstructionRetrieval | InstructionReranking | text | eng |
| Robust04InstructionRetrieval | InstructionReranking | text | eng |
| KorHateSpeechMLClassification | MultilabelClassification | text | kor |
| MalteseNewsClassification | MultilabelClassification | text | mlt |
| MultiEURLEXMultilabelClassification | MultilabelClassification | text | bul, ces, dan, deu, ell, ... (23) |
| BrazilianToxicTweetsClassification | MultilabelClassification | text | por |
| CEDRClassification | MultilabelClassification | text | rus |
| CTKFactsNLI | PairClassification | text | ces |
| SprintDuplicateQuestions | PairClassification | text | eng |
| TwitterURLCorpus | PairClassification | text | eng |
| ArmenianParaphrasePC | PairClassification | text | hye |
| indonli | PairClassification | text | ind |
| OpusparcusPC | PairClassification | text | deu, eng, fin, fra, rus, ... (6) |
| PawsXPairClassification | PairClassification | text | cmn, deu, eng, fra, jpn, ... (7) |
| RTE3 | PairClassification | text | deu, eng, fra, ita |
| XNLI | PairClassification | text | ara, bul, deu, ell, eng, ... (14) |
| PpcPC | PairClassification | text | pol |
| TERRa | PairClassification | text | rus |
| WebLINXCandidatesReranking | Reranking | text | eng |
| AlloprofReranking | Reranking | text | fra |
| VoyageMMarcoReranking | Reranking | text | jpn |
| WikipediaRerankingMultilingual | Reranking | text | ben, bul, ces, dan, deu, ... (18) |
| RuBQReranking | Reranking | text | rus |
| T2Reranking | Reranking | text | cmn |
| GermanSTSBenchmark | STS | text | deu |
| SICK-R | STS | text | eng |
| STS12 | STS | text | eng |
| STS13 | STS | text | eng |
| STS14 | STS | text | eng |
| STS15 | STS | text | eng |
| STSBenchmark | STS | text | eng |
| FaroeseSTS | STS | text | fao |
| FinParaSTS | STS | text | fin |
| JSICK | STS | text | jpn |
| IndicCrosslingualSTS | STS | text | asm, ben, eng, guj, hin, ... (13) |
| SemRel24STS | STS | text | afr, amh, arb, arq, ary, ... (12) |
| STS17 | STS | text | ara, deu, eng, fra, ita, ... (9) |
| STS22.v2 | STS | text | ara, cmn, deu, eng, fra, ... (10) |
| STSES | STS | text | spa |
| STSB | STS | text | cmn |
| MIRACLRetrievalHardNegatives | Retrieval | text | ara, ben, deu, eng, fas, ... (18) |
Citation
@article{enevoldsen2025mmtebmassivemultilingualtext,
author = {Kenneth Enevoldsen and Isaac Chung and Imene Kerboua and Márton Kardos and Ashwin Mathur and David Stap and Jay Gala and Wissam Siblini and Dominik Krzemiński and Genta Indra Winata and Saba Sturua and Saiteja Utpala and Mathieu Ciancone and Marion Schaeffer and Gabriel Sequeira and Diganta Misra and Shreeya Dhakal and Jonathan Rystrøm and Roman Solomatin and Ömer Çağatan and Akash Kundu and Martin Bernstorff and Shitao Xiao and Akshita Sukhlecha and Bhavish Pahwa and Rafał Poświata and Kranthi Kiran GV and Shawon Ashraf and Daniel Auras and Björn Plüster and Jan Philipp Harries and Loïc Magne and Isabelle Mohr and Mariya Hendriksen and Dawei Zhu and Hippolyte Gisserot-Boukhlef and Tom Aarsen and Jan Kostkan and Konrad Wojtasik and Taemin Lee and Marek Šuppa and Crystina Zhang and Roberta Rocca and Mohammed Hamdy and Andrianos Michail and John Yang and Manuel Faysse and Aleksei Vatolin and Nandan Thakur and Manan Dey and Dipam Vasani and Pranjal Chitale and Simone Tedeschi and Nguyen Tai and Artem Snegirev and Michael Günther and Mengzhou Xia and Weijia Shi and Xing Han Lù and Jordan Clive and Gayatri Krishnakumar and Anna Maksimova and Silvan Wehrli and Maria Tikhonova and Henil Panchal and Aleksandr Abramov and Malte Ostendorff and Zheng Liu and Simon Clematide and Lester James Miranda and Alena Fenogenova and Guangyu Song and Ruqiya Bin Safi and Wen-Ding Li and Alessia Borghini and Federico Cassano and Hongjin Su and Jimmy Lin and Howard Yen and Lasse Hansen and Sara Hooker and Chenghao Xiao and Vaibhav Adlakha and Orion Weller and Siva Reddy and Niklas Muennighoff},
doi = {10.48550/arXiv.2502.13595},
journal = {arXiv preprint arXiv:2502.13595},
publisher = {arXiv},
title = {MMTEB: Massive Multilingual Text Embedding Benchmark},
url = {https://arxiv.org/abs/2502.13595},
year = {2025},
}
MTEB(Scandinavian, v1)¶
Scandinavian text embedding quality covering Danish, Swedish, Norwegian Bokmål, and Nynorsk and spanning classification, clustering, retrieval as well as bitext tasks across dialects or written forms.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| BornholmBitextMining | BitextMining | text | dan |
| NorwegianCourtsBitextMining | BitextMining | text | nno, nob |
| AngryTweetsClassification | Classification | text | dan |
| DanishPoliticalCommentsClassification | Classification | text | dan |
| DalajClassification | Classification | text | swe |
| DKHateClassification | Classification | text | dan |
| LccSentimentClassification | Classification | text | dan |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MassiveScenarioClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| NordicLangClassification | Classification | text | dan, fao, isl, nno, nob, ... (6) |
| NoRecClassification | Classification | text | nob |
| NorwegianParliamentClassification | Classification | text | nob |
| ScalaClassification | Classification | text | dan, nno, nob, swe |
| SwedishSentimentClassification | Classification | text | swe |
| SweRecClassification | Classification | text | swe |
| DanFeverRetrieval | Retrieval | text | dan |
| NorQuadRetrieval | Retrieval | text | nob |
| SNLRetrieval | Retrieval | text | nob |
| SwednRetrieval | Retrieval | text | swe |
| SweFaqRetrieval | Retrieval | text | swe |
| TV2Nordretrieval | Retrieval | text | dan |
| TwitterHjerneRetrieval | Retrieval | text | dan |
| SNLHierarchicalClusteringS2S | Clustering | text | nob |
| SNLHierarchicalClusteringP2P | Clustering | text | nob |
| SwednClusteringP2P | Clustering | text | swe |
| SwednClusteringS2S | Clustering | text | swe |
| VGHierarchicalClusteringS2S | Clustering | text | nob |
| VGHierarchicalClusteringP2P | Clustering | text | nob |
Citation
@article{enevoldsenScandinavianEmbeddingBenchmarks2024,
author = {Enevoldsen, Kenneth and Kardos, Márton and Muennighoff, Niklas and Nielbo, Kristoffer},
language = {en},
month = feb,
shorttitle = {The {Scandinavian} {Embedding} {Benchmarks}},
title = {The {Scandinavian} {Embedding} {Benchmarks}: {Comprehensive} {Assessment} of {Multilingual} and {Monolingual} {Text} {Embedding}},
url = {https://openreview.net/forum?id=pJl_i7HIA72},
urldate = {2024-04-12},
year = {2024},
}
MTEB(cmn, v1)¶
Chinese text embedding quality across retrieval, reranking, pair classification, clustering, classification, and semantic similarity.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| T2Retrieval | Retrieval | text | cmn |
| MMarcoRetrieval | Retrieval | text | cmn |
| DuRetrieval | Retrieval | text | cmn |
| CovidRetrieval | Retrieval | text | cmn |
| CmedqaRetrieval | Retrieval | text | cmn |
| EcomRetrieval | Retrieval | text | cmn |
| MedicalRetrieval | Retrieval | text | cmn |
| VideoRetrieval | Retrieval | text | cmn |
| T2Reranking | Reranking | text | cmn |
| MMarcoReranking | Reranking | text | cmn |
| CMedQAv1-reranking | Reranking | text | cmn |
| CMedQAv2-reranking | Reranking | text | cmn |
| Ocnli | PairClassification | text | cmn |
| Cmnli | PairClassification | text | cmn |
| CLSClusteringS2S | Clustering | text | cmn |
| CLSClusteringP2P | Clustering | text | cmn |
| ThuNewsClusteringS2S | Clustering | text | cmn |
| ThuNewsClusteringP2P | Clustering | text | cmn |
| LCQMC | STS | text | cmn |
| PAWSX | STS | text | cmn |
| AFQMC | STS | text | cmn |
| QBQTC | STS | text | cmn |
| TNews | Classification | text | cmn |
| IFlyTek | Classification | text | cmn |
| Waimai | Classification | text | cmn |
| OnlineShopping | Classification | text | cmn |
| JDReview | Classification | text | cmn |
| MultilingualSentiment | Classification | text | cmn |
| ATEC | STS | text | cmn |
| BQ | STS | text | cmn |
| STSB | STS | text | cmn |
Citation
@inproceedings{xiao2024cpackpackedresourcesgeneral,
author = {Xiao, Shitao and Liu, Zheng and Zhang, Peitian and Muennighoff, Niklas and Lian, Defu and Nie, Jian-Yun},
booktitle = {Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval},
collection = {SIGIR 2024},
doi = {10.1145/3626772.3657878},
month = {July},
pages = {641–649},
publisher = {ACM},
series = {SIGIR 2024},
title = {C-Pack: Packed Resources For General Chinese Embeddings},
url = {https://doi.org/10.1145/3626772.3657878},
year = {2024},
}
MTEB(deu, v1)¶
German text embedding quality across classification, clustering, pair classification, reranking, retrieval, and semantic similarity.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| AmazonCounterfactualClassification | Classification | text | deu, eng, jpn |
| AmazonReviewsClassification | Classification | text | cmn, deu, eng, fra, jpn, ... (6) |
| MTOPDomainClassification | Classification | text | deu, eng, fra, hin, spa, ... (6) |
| MTOPIntentClassification | Classification | text | deu, eng, fra, hin, spa, ... (6) |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MassiveScenarioClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| BlurbsClusteringP2P | Clustering | text | deu |
| BlurbsClusteringS2S | Clustering | text | deu |
| TenKGnadClusteringP2P | Clustering | text | deu |
| TenKGnadClusteringS2S | Clustering | text | deu |
| FalseFriendsGermanEnglish | PairClassification | text | deu |
| PawsXPairClassification | PairClassification | text | cmn, deu, eng, fra, jpn, ... (7) |
| MIRACLReranking | Reranking | text | ara, ben, deu, eng, fas, ... (18) |
| GermanQuAD-Retrieval | Retrieval | text | deu |
| GermanDPR | Retrieval | text | deu |
| XMarket | Retrieval | text | deu, eng, spa |
| GerDaLIR | Retrieval | text | deu |
| GermanSTSBenchmark | STS | text | deu |
| STS22 | STS | text | ara, cmn, deu, eng, fra, ... (10) |
Citation
@inproceedings{wehrli2024germantextembeddingclustering,
address = {Ingolstadt, Germany},
archiveprefix = {arXiv},
author = {Wehrli, Silvan and Arnrich, Bert and Irrgang, Christopher},
booktitle = {Proceedings of the 19th Conference on Natural Language Processing ({KONVENS} 2023)},
editor = {Georges, Munir and Herygers, Aaricia and Friedrich, Annemarie and Roth, Benjamin},
eprint = {2401.02709},
month = {sep},
pages = {187--201},
publisher = {Association for Computational Lingustics},
title = {{G}erman Text Embedding Clustering Benchmark},
url = {https://aclanthology.org/2023.konvens-main.20/},
year = {2023},
}
MTEB(eng, v1)¶
English text embedding quality across classification, clustering, retrieval, reranking, pair classification, and semantic similarity. We recommend using MTEB(eng, v2) instead, which resolves a known scoring bug, uses updated task versions, and removes common fine-tuning datasets such as MSMARCO for more comparable scores.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| AmazonPolarityClassification | Classification | text | eng |
| AmazonReviewsClassification | Classification | text | cmn, deu, eng, fra, jpn, ... (6) |
| ArguAna | Retrieval | text | eng |
| ArxivClusteringP2P | Clustering | text | eng |
| ArxivClusteringS2S | Clustering | text | eng |
| AskUbuntuDupQuestions | Reranking | text | eng |
| BIOSSES | STS | text | eng |
| Banking77Classification | Classification | text | eng |
| BiorxivClusteringP2P | Clustering | text | eng |
| BiorxivClusteringS2S | Clustering | text | eng |
| CQADupstackRetrieval | Retrieval | text | eng |
| ClimateFEVER | Retrieval | text | eng |
| DBPedia | Retrieval | text | eng |
| EmotionClassification | Classification | text | eng |
| FEVER | Retrieval | text | eng |
| FiQA2018 | Retrieval | text | eng |
| HotpotQA | Retrieval | text | eng |
| ImdbClassification | Classification | text | eng |
| MTOPDomainClassification | Classification | text | deu, eng, fra, hin, spa, ... (6) |
| MTOPIntentClassification | Classification | text | deu, eng, fra, hin, spa, ... (6) |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MassiveScenarioClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MedrxivClusteringP2P | Clustering | text | eng |
| MedrxivClusteringS2S | Clustering | text | eng |
| MindSmallReranking | Reranking | text | eng |
| NFCorpus | Retrieval | text | eng |
| NQ | Retrieval | text | eng |
| QuoraRetrieval | Retrieval | text | eng |
| RedditClustering | Clustering | text | eng |
| RedditClusteringP2P | Clustering | text | eng |
| SCIDOCS | Retrieval | text | eng |
| SICK-R | STS | text | eng |
| STS12 | STS | text | eng |
| STS13 | STS | text | eng |
| STS14 | STS | text | eng |
| STS15 | STS | text | eng |
| STS16 | STS | text | eng |
| STSBenchmark | STS | text | eng |
| SciDocsRR | Reranking | text | eng |
| SciFact | Retrieval | text | eng |
| SprintDuplicateQuestions | PairClassification | text | eng |
| StackExchangeClustering | Clustering | text | eng |
| StackExchangeClusteringP2P | Clustering | text | eng |
| StackOverflowDupQuestions | Reranking | text | eng |
| SummEval | Summarization | text | eng |
| TRECCOVID | Retrieval | text | eng |
| Touche2020 | Retrieval | text | eng |
| ToxicConversationsClassification | Classification | text | eng |
| TweetSentimentExtractionClassification | Classification | text | eng |
| TwentyNewsgroupsClustering | Clustering | text | eng |
| TwitterSemEval2015 | PairClassification | text | eng |
| TwitterURLCorpus | PairClassification | text | eng |
| MSMARCO | Retrieval | text | eng |
| AmazonCounterfactualClassification | Classification | text | deu, eng, jpn |
| STS17 | STS | text | ara, deu, eng, fra, ita, ... (9) |
| STS22 | STS | text | ara, cmn, deu, eng, fra, ... (10) |
Citation
@inproceedings{muennighoff2022mteb,
address = {Dubrovnik, Croatia},
author = {Muennighoff, Niklas and Tazi, Nouamane and Magne, Loic and Reimers, Nils},
booktitle = {Proceedings of the 17th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics},
doi = {10.18653/v1/2023.eacl-main.148},
editor = {Vlachos, Andreas and Augenstein, Isabelle},
month = {may},
pages = {2014--2037},
publisher = {Association for Computational Linguistics},
title = {{MTEB}: Massive Text Embedding Benchmark},
url = {https://aclanthology.org/2023.eacl-main.148/},
year = {2023},
}
MTEB(eng, v2)¶
English text embedding quality across classification, clustering, retrieval, reranking, pair classification, and semantic similarity, prioritizing tasks not commonly used for fine-tuning to give a more realistic estimate of generalization performance. The original v1 leaderboard is available under MTEB(eng, v1).
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| ArguAna | Retrieval | text | eng |
| ArXivHierarchicalClusteringP2P | Clustering | text | eng |
| ArXivHierarchicalClusteringS2S | Clustering | text | eng |
| AskUbuntuDupQuestions | Reranking | text | eng |
| BIOSSES | STS | text | eng |
| Banking77Classification | Classification | text | eng |
| BiorxivClusteringP2P.v2 | Clustering | text | eng |
| CQADupstackGamingRetrieval | Retrieval | text | eng |
| CQADupstackUnixRetrieval | Retrieval | text | eng |
| ClimateFEVERHardNegatives | Retrieval | text | eng |
| FEVERHardNegatives | Retrieval | text | eng |
| FiQA2018 | Retrieval | text | eng |
| HotpotQAHardNegatives | Retrieval | text | eng |
| ImdbClassification | Classification | text | eng |
| MTOPDomainClassification | Classification | text | deu, eng, fra, hin, spa, ... (6) |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MassiveScenarioClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MedrxivClusteringP2P.v2 | Clustering | text | eng |
| MedrxivClusteringS2S.v2 | Clustering | text | eng |
| MindSmallReranking | Reranking | text | eng |
| SCIDOCS | Retrieval | text | eng |
| SICK-R | STS | text | eng |
| STS12 | STS | text | eng |
| STS13 | STS | text | eng |
| STS14 | STS | text | eng |
| STS15 | STS | text | eng |
| STSBenchmark | STS | text | eng |
| SprintDuplicateQuestions | PairClassification | text | eng |
| StackExchangeClustering.v2 | Clustering | text | eng |
| StackExchangeClusteringP2P.v2 | Clustering | text | eng |
| TRECCOVID | Retrieval | text | eng |
| Touche2020Retrieval.v3 | Retrieval | text | eng |
| ToxicConversationsClassification | Classification | text | eng |
| TweetSentimentExtractionClassification | Classification | text | eng |
| TwentyNewsgroupsClustering.v2 | Clustering | text | eng |
| TwitterSemEval2015 | PairClassification | text | eng |
| TwitterURLCorpus | PairClassification | text | eng |
| SummEvalSummarization.v2 | Summarization | text | eng |
| AmazonCounterfactualClassification | Classification | text | deu, eng, jpn |
| STS17 | STS | text | ara, deu, eng, fra, ita, ... (9) |
| STS22.v2 | STS | text | ara, cmn, deu, eng, fra, ... (10) |
Citation
@article{enevoldsen2025mmtebmassivemultilingualtext,
author = {Kenneth Enevoldsen and Isaac Chung and Imene Kerboua and Márton Kardos and Ashwin Mathur and David Stap and Jay Gala and Wissam Siblini and Dominik Krzemiński and Genta Indra Winata and Saba Sturua and Saiteja Utpala and Mathieu Ciancone and Marion Schaeffer and Gabriel Sequeira and Diganta Misra and Shreeya Dhakal and Jonathan Rystrøm and Roman Solomatin and Ömer Çağatan and Akash Kundu and Martin Bernstorff and Shitao Xiao and Akshita Sukhlecha and Bhavish Pahwa and Rafał Poświata and Kranthi Kiran GV and Shawon Ashraf and Daniel Auras and Björn Plüster and Jan Philipp Harries and Loïc Magne and Isabelle Mohr and Mariya Hendriksen and Dawei Zhu and Hippolyte Gisserot-Boukhlef and Tom Aarsen and Jan Kostkan and Konrad Wojtasik and Taemin Lee and Marek Šuppa and Crystina Zhang and Roberta Rocca and Mohammed Hamdy and Andrianos Michail and John Yang and Manuel Faysse and Aleksei Vatolin and Nandan Thakur and Manan Dey and Dipam Vasani and Pranjal Chitale and Simone Tedeschi and Nguyen Tai and Artem Snegirev and Michael Günther and Mengzhou Xia and Weijia Shi and Xing Han Lù and Jordan Clive and Gayatri Krishnakumar and Anna Maksimova and Silvan Wehrli and Maria Tikhonova and Henil Panchal and Aleksandr Abramov and Malte Ostendorff and Zheng Liu and Simon Clematide and Lester James Miranda and Alena Fenogenova and Guangyu Song and Ruqiya Bin Safi and Wen-Ding Li and Alessia Borghini and Federico Cassano and Hongjin Su and Jimmy Lin and Howard Yen and Lasse Hansen and Sara Hooker and Chenghao Xiao and Vaibhav Adlakha and Orion Weller and Siva Reddy and Niklas Muennighoff},
doi = {10.48550/arXiv.2502.13595},
journal = {arXiv preprint arXiv:2502.13595},
publisher = {arXiv},
title = {MMTEB: Massive Multilingual Text Embedding Benchmark},
url = {https://arxiv.org/abs/2502.13595},
year = {2025},
}
MTEB(fas, v1)¶
Persian text embedding quality across classification, clustering, pair classification, reranking, retrieval, semantic similarity, and summarization retrieval.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| PersianFoodSentimentClassification | Classification | text | fas |
| SynPerChatbotConvSAClassification | Classification | text | fas |
| SynPerChatbotConvSAToneChatbotClassification | Classification | text | fas |
| SynPerChatbotConvSAToneUserClassification | Classification | text | fas |
| SynPerChatbotSatisfactionLevelClassification | Classification | text | fas |
| SynPerChatbotRAGToneChatbotClassification | Classification | text | fas |
| SynPerChatbotRAGToneUserClassification | Classification | text | fas |
| SynPerChatbotToneChatbotClassification | Classification | text | fas |
| SynPerChatbotToneUserClassification | Classification | text | fas |
| SynPerTextToneClassification | Classification | text | fas |
| SIDClassification | Classification | text | fas |
| DeepSentiPers | Classification | text | fas |
| PersianTextEmotion | Classification | text | fas |
| SentimentDKSF | Classification | text | fas |
| NLPTwitterAnalysisClassification | Classification | text | fas |
| DigikalamagClassification | Classification | text | fas |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MassiveScenarioClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| BeytooteClustering | Clustering | text | fas |
| DigikalamagClustering | Clustering | text | fas |
| HamshahriClustring | Clustering | text | fas |
| NLPTwitterAnalysisClustering | Clustering | text | fas |
| SIDClustring | Clustering | text | fas |
| FarsTail | PairClassification | text | fas |
| CExaPPC | PairClassification | text | fas |
| SynPerChatbotRAGFAQPC | PairClassification | text | fas |
| FarsiParaphraseDetection | PairClassification | text | fas |
| SynPerTextKeywordsPC | PairClassification | text | fas |
| SynPerQAPC | PairClassification | text | fas |
| ParsinluEntail | PairClassification | text | fas |
| ParsinluQueryParaphPC | PairClassification | text | fas |
| MIRACLReranking | Reranking | text | ara, ben, deu, eng, fas, ... (18) |
| WikipediaRerankingMultilingual | Reranking | text | ben, bul, ces, dan, deu, ... (18) |
| SynPerQARetrieval | Retrieval | text | fas |
| SynPerChatbotTopicsRetrieval | Retrieval | text | fas |
| SynPerChatbotRAGTopicsRetrieval | Retrieval | text | fas |
| SynPerChatbotRAGFAQRetrieval | Retrieval | text | fas |
| PersianWebDocumentRetrieval | Retrieval | text | fas |
| WikipediaRetrievalMultilingual | Retrieval | text | ben, bul, ces, dan, deu, ... (16) |
| MIRACLRetrieval | Retrieval | text | ara, ben, deu, eng, fas, ... (18) |
| ClimateFEVER-Fa | Retrieval | text | fas |
| DBPedia-Fa | Retrieval | text | fas |
| HotpotQA-Fa | Retrieval | text | fas |
| MSMARCO-Fa | Retrieval | text | fas |
| NQ-Fa | Retrieval | text | fas |
| ArguAna-Fa | Retrieval | text | fas |
| CQADupstackRetrieval-Fa | Retrieval | text | fas |
| FiQA2018-Fa | Retrieval | text | fas |
| NFCorpus-Fa | Retrieval | text | fas |
| QuoraRetrieval-Fa | Retrieval | text | fas |
| SCIDOCS-Fa | Retrieval | text | fas |
| SciFact-Fa | Retrieval | text | fas |
| TRECCOVID-Fa | Retrieval | text | fas |
| Touche2020-Fa | Retrieval | text | fas |
| Farsick | STS | text | fas |
| SynPerSTS | STS | text | fas |
| Query2Query | STS | text | fas |
| SAMSumFa | BitextMining | text | fas |
| SynPerChatbotSumSRetrieval | BitextMining | text | fas |
| SynPerChatbotRAGSumSRetrieval | BitextMining | text | fas |
Citation
@inproceedings{zinvandi2025famteb,
address = {Suzhou, China},
author = {Zinvandi, Erfan and Alikhani, Morteza and Sarmadi, Mehran and Pourbahman, Zahra and Arvin, Sepehr and Kazemi, Reza and Amini, Arash},
booktitle = {Findings of the {A}ssociation for {C}omputational {L}inguistics: {EMNLP} 2025},
doi = {10.18653/v1/2025.findings-emnlp.614},
editor = {Christodoulopoulos, Christos and Chakraborty, Tanmoy and Rose, Carolyn and Peng, Violet},
isbn = {979-8-89176-335-7},
month = {nov},
pages = {11441--11468},
publisher = {Association for Computational Linguistics},
title = {{F}a{MTEB}: Massive Text Embedding Benchmark in {P}ersian Language},
url = {https://aclanthology.org/2025.findings-emnlp.614/},
year = {2025},
}
MTEB(fas, v2)¶
Persian text embedding quality across classification, clustering, pair classification, reranking, retrieval, semantic similarity, and summarization retrieval. In v2, large datasets were optimized for accessibility, low-quality datasets were removed, and higher-quality data was added; see the main PR for details.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| PersianFoodSentimentClassification | Classification | text | fas |
| SynPerChatbotConvSAClassification | Classification | text | fas |
| SynPerChatbotConvSAToneChatbotClassification | Classification | text | fas |
| SynPerChatbotConvSAToneUserClassification | Classification | text | fas |
| SynPerChatbotSatisfactionLevelClassification | Classification | text | fas |
| SynPerTextToneClassification.v3 | Classification | text | fas |
| SIDClassification.v2 | Classification | text | fas |
| DeepSentiPers.v2 | Classification | text | fas |
| PersianTextEmotion.v2 | Classification | text | fas |
| NLPTwitterAnalysisClassification.v2 | Classification | text | fas |
| DigikalamagClassification | Classification | text | fas |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MassiveScenarioClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| StyleClassification | Classification | text | fas |
| PerShopDomainClassification | Classification | text | fas |
| PerShopIntentClassification | Classification | text | fas |
| BeytooteClustering | Clustering | text | fas |
| DigikalamagClustering | Clustering | text | fas |
| HamshahriClustring | Clustering | text | fas |
| NLPTwitterAnalysisClustering | Clustering | text | fas |
| SIDClustring | Clustering | text | fas |
| FarsTail | PairClassification | text | fas |
| SynPerChatbotRAGFAQPC | PairClassification | text | fas |
| FarsiParaphraseDetection | PairClassification | text | fas |
| SynPerTextKeywordsPC | PairClassification | text | fas |
| SynPerQAPC | PairClassification | text | fas |
| ParsinluEntail | PairClassification | text | fas |
| ParsinluQueryParaphPC | PairClassification | text | fas |
| MIRACLReranking | Reranking | text | ara, ben, deu, eng, fas, ... (18) |
| WikipediaRerankingMultilingual | Reranking | text | ben, bul, ces, dan, deu, ... (18) |
| SynPerQARetrieval | Retrieval | text | fas |
| SynPerChatbotRAGFAQRetrieval | Retrieval | text | fas |
| PersianWebDocumentRetrieval | Retrieval | text | fas |
| WikipediaRetrievalMultilingual | Retrieval | text | ben, bul, ces, dan, deu, ... (16) |
| MIRACLRetrievalHardNegatives | Retrieval | text | ara, ben, deu, eng, fas, ... (18) |
| HotpotQA-FaHardNegatives | Retrieval | text | fas |
| MSMARCO-FaHardNegatives | Retrieval | text | fas |
| NQ-FaHardNegatives | Retrieval | text | fas |
| ArguAna-Fa.v2 | Retrieval | text | fas |
| FiQA2018-Fa.v2 | Retrieval | text | fas |
| QuoraRetrieval-Fa.v2 | Retrieval | text | fas |
| SCIDOCS-Fa.v2 | Retrieval | text | fas |
| SciFact-Fa.v2 | Retrieval | text | fas |
| TRECCOVID-Fa.v2 | Retrieval | text | fas |
| FEVER-FaHardNegatives | Retrieval | text | fas |
| NeuCLIR2023RetrievalHardNegatives | Retrieval | text | fas, rus, zho |
| WebFAQRetrieval | Retrieval | text | ara, aze, ben, bul, cat, ... (51) |
| Farsick | STS | text | fas |
| SynPerSTS | STS | text | fas |
| SAMSumFa | BitextMining | text | fas |
| SynPerChatbotSumSRetrieval | BitextMining | text | fas |
| SynPerChatbotRAGSumSRetrieval | BitextMining | text | fas |
Citation
@inproceedings{zinvandi2025famteb,
address = {Suzhou, China},
author = {Zinvandi, Erfan and Alikhani, Morteza and Sarmadi, Mehran and Pourbahman, Zahra and Arvin, Sepehr and Kazemi, Reza and Amini, Arash},
booktitle = {Findings of the {A}ssociation for {C}omputational {L}inguistics: {EMNLP} 2025},
doi = {10.18653/v1/2025.findings-emnlp.614},
editor = {Christodoulopoulos, Christos and Chakraborty, Tanmoy and Rose, Carolyn and Peng, Violet},
isbn = {979-8-89176-335-7},
month = {nov},
pages = {11441--11468},
publisher = {Association for Computational Linguistics},
title = {{F}a{MTEB}: Massive Text Embedding Benchmark in {P}ersian Language},
url = {https://aclanthology.org/2025.findings-emnlp.614/},
year = {2025},
}
MTEB(fra, v1)¶
French text embedding quality across classification, clustering, pair classification, reranking, retrieval, and semantic similarity, using high-quality native French datasets.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| AmazonReviewsClassification | Classification | text | cmn, deu, eng, fra, jpn, ... (6) |
| MasakhaNEWSClassification | Classification | text | amh, eng, fra, hau, ibo, ... (16) |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MassiveScenarioClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MTOPDomainClassification | Classification | text | deu, eng, fra, hin, spa, ... (6) |
| MTOPIntentClassification | Classification | text | deu, eng, fra, hin, spa, ... (6) |
| AlloProfClusteringP2P | Clustering | text | fra |
| AlloProfClusteringS2S | Clustering | text | fra |
| HALClusteringS2S | Clustering | text | fra |
| MasakhaNEWSClusteringP2P | Clustering | text | amh, eng, fra, hau, ibo, ... (16) |
| MasakhaNEWSClusteringS2S | Clustering | text | amh, eng, fra, hau, ibo, ... (16) |
| MLSUMClusteringP2P | Clustering | text | deu, fra, rus, spa |
| MLSUMClusteringS2S | Clustering | text | deu, fra, rus, spa |
| PawsXPairClassification | PairClassification | text | cmn, deu, eng, fra, jpn, ... (7) |
| AlloprofReranking | Reranking | text | fra |
| SyntecReranking | Reranking | text | fra |
| AlloprofRetrieval | Retrieval | text | fra |
| BSARDRetrieval | Retrieval | text | fra |
| MintakaRetrieval | Retrieval | text | ara, deu, fra, hin, ita, ... (8) |
| SyntecRetrieval | Retrieval | text | fra |
| XPQARetrieval | Retrieval | text | ara, cmn, deu, eng, fra, ... (13) |
| SICKFr | STS | text | fra |
| STSBenchmarkMultilingualSTS | STS | text | cmn, deu, eng, fra, ita, ... (10) |
| SummEvalFr | Summarization | text | fra |
| STS22 | STS | text | ara, cmn, deu, eng, fra, ... (10) |
Citation
@misc{ciancone2024mteb,
archiveprefix = {arXiv},
author = {Mathieu Ciancone and Imene Kerboua and Marion Schaeffer and Wissam Siblini},
eprint = {2405.20468},
primaryclass = {cs.CL},
title = {MTEB-French: Resources for French Sentence Embedding Evaluation and Analysis},
url = {https://arxiv.org/abs/2405.20468},
year = {2024},
}
MTEB(jpn, v1)¶
Japanese text embedding quality across clustering, classification, semantic similarity, pair classification, retrieval, and reranking.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| LivedoorNewsClustering.v2 | Clustering | text | jpn |
| MewsC16JaClustering | Clustering | text | jpn |
| AmazonReviewsClassification | Classification | text | cmn, deu, eng, fra, jpn, ... (6) |
| AmazonCounterfactualClassification | Classification | text | deu, eng, jpn |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MassiveScenarioClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| JSTS | STS | text | jpn |
| JSICK | STS | text | jpn |
| PawsXPairClassification | PairClassification | text | cmn, deu, eng, fra, jpn, ... (7) |
| JaqketRetrieval | Retrieval | text | jpn |
| MrTidyRetrieval | Retrieval | text | ara, ben, eng, fin, ind, ... (11) |
| JaGovFaqsRetrieval | Retrieval | text | jpn |
| NLPJournalTitleAbsRetrieval | Retrieval | text | jpn |
| NLPJournalAbsIntroRetrieval | Retrieval | text | jpn |
| NLPJournalTitleIntroRetrieval | Retrieval | text | jpn |
| ESCIReranking | Reranking | text | eng, jpn, spa |
MTEB(kor, v1)¶
Korean text embedding quality across classification, reranking, retrieval, and semantic similarity.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| KLUE-TC | Classification | text | kor |
| MIRACLReranking | Reranking | text | ara, ben, deu, eng, fas, ... (18) |
| MIRACLRetrieval | Retrieval | text | ara, ben, deu, eng, fas, ... (18) |
| Ko-StrategyQA | Retrieval | text | kor |
| KLUE-STS | STS | text | kor |
| KorSTS | STS | text | kor |
MTEB(kor, v2)¶
Korean text embedding quality across classification, clustering, pair classification (NLI), reranking, retrieval, and semantic similarity. Expanded successor to MTEB(kor, v1): grows the suite from 6 to 20 tasks, adding clustering (SIB200, KLUE-MRC domain/category), pair classification/NLI (KLUE-NLI, KorNLI, PawsX), additional retrieval (LawIRKo, SQuAD-Ko, AutoRAG, PublicHealthQA, Belebele, MultiLongDoc, MrTidy) and STS17, for broader and more robust coverage of Korean embedding capabilities.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| KLUE-TC | Classification | text | kor |
| SIB200ClusteringS2S | Clustering | text | ace, acm, acq, aeb, afr, ... (197) |
| KlueMrcDomainClustering | Clustering | text | kor |
| KlueYnatMrcCategoryClustering | Clustering | text | kor |
| KLUE-NLI | PairClassification | text | kor |
| KorNLI | PairClassification | text | kor |
| PawsXPairClassification | PairClassification | text | cmn, deu, eng, fra, jpn, ... (7) |
| MIRACLReranking | Reranking | text | ara, ben, deu, eng, fas, ... (18) |
| MIRACLRetrieval | Retrieval | text | ara, ben, deu, eng, fas, ... (18) |
| Ko-StrategyQA | Retrieval | text | kor |
| LawIRKo | Retrieval | text | kor |
| SQuADKorV1Retrieval | Retrieval | text | kor |
| AutoRAGRetrieval | Retrieval | text | kor |
| PublicHealthQA | Retrieval | text | ara, eng, fra, kor, rus, ... (8) |
| BelebeleRetrieval | Retrieval | text | acm, afr, als, amh, apc, ... (115) |
| MultiLongDocRetrieval | Retrieval | text | ara, cmn, deu, eng, fra, ... (13) |
| MrTidyRetrieval | Retrieval | text | ara, ben, eng, fin, ind, ... (11) |
| KLUE-STS | STS | text | kor |
| KorSTS | STS | text | kor |
| STS17 | STS | text | ara, deu, eng, fra, ita, ... (9) |
MTEB(nld, v1)¶
Dutch text embedding quality across classification, clustering, pair classification, multilabel classification, reranking, retrieval, and semantic similarity.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| DutchBookReviewSentimentClassification.v2 | Classification | text | nld |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MassiveScenarioClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| SIB200Classification | Classification | text | ace, acm, acq, aeb, afr, ... (197) |
| MultiHateClassification | Classification | text | ara, cmn, deu, eng, fra, ... (11) |
| VaccinChatNLClassification | Classification | text | nld |
| DutchColaClassification | Classification | text | nld |
| DutchGovernmentBiasClassification | Classification | text | nld |
| DutchSarcasticHeadlinesClassification | Classification | text | nld |
| DutchNewsArticlesClassification | Classification | text | nld |
| OpenTenderClassification | Classification | text | nld |
| IconclassClassification | Classification | text | nld |
| SICKNLPairClassification | PairClassification | text | nld |
| XLWICNLPairClassification | PairClassification | text | nld |
| CovidDisinformationNLMultiLabelClassification | MultilabelClassification | text | nld |
| MultiEURLEXMultilabelClassification | MultilabelClassification | text | bul, ces, dan, deu, ell, ... (23) |
| VABBMultiLabelClassification | MultilabelClassification | text | nld |
| DutchNewsArticlesClusteringS2S | Clustering | text | nld |
| DutchNewsArticlesClusteringP2P | Clustering | text | nld |
| SIB200ClusteringS2S | Clustering | text | ace, acm, acq, aeb, afr, ... (197) |
| VABBClusteringS2S | Clustering | text | nld |
| VABBClusteringP2P | Clustering | text | nld |
| OpenTenderClusteringS2S | Clustering | text | nld |
| OpenTenderClusteringP2P | Clustering | text | nld |
| IconclassClusteringS2S | Clustering | text | nld |
| WikipediaRerankingMultilingual | Reranking | text | ben, bul, ces, dan, deu, ... (18) |
| ArguAna-NL.v2 | Retrieval | text | nld |
| SCIDOCS-NL.v2 | Retrieval | text | nld |
| SciFact-NL.v2 | Retrieval | text | nld |
| NFCorpus-NL.v2 | Retrieval | text | nld |
| BelebeleRetrieval | Retrieval | text | acm, afr, als, amh, apc, ... (115) |
| WebFAQRetrieval | Retrieval | text | ara, aze, ben, bul, cat, ... (51) |
| DutchNewsArticlesRetrieval | Retrieval | text | nld |
| bBSARDNLRetrieval | Retrieval | text | nld |
| LegalQANLRetrieval | Retrieval | text | nld |
| OpenTenderRetrieval | Retrieval | text | nld |
| VABBRetrieval | Retrieval | text | nld |
| WikipediaRetrievalMultilingual | Retrieval | text | ben, bul, ces, dan, deu, ... (16) |
| SICK-NL-STS | STS | text | nld |
| STSBenchmarkMultilingualSTS | STS | text | cmn, deu, eng, fra, ita, ... (10) |
Citation
@inproceedings{banar2025mtebnle5nlembeddingbenchmark,
address = {San Diego, California, United States},
author = {Banar, Nikolay and Lotfi, Ehsan and Van Nooten, Jens and Arhiliuc, Cristina and Kliocaite, Marija and Daelemans, Walter},
booktitle = {Findings of the {A}ssociation for {C}omputational {L}inguistics: {ACL} 2026},
doi = {10.18653/v1/2026.findings-acl.1236},
editor = {Liakata, Maria and Moreira, Viviane P. and Zhang, Jiajun and Jurgens, David},
isbn = {979-8-89176-395-1},
month = {jul},
pages = {24684--24709},
publisher = {Association for Computational Linguistics},
title = {{MTEB}-{NL} and {E}5-{NL}: Embedding Benchmark and Models for {D}utch},
url = {https://aclanthology.org/2026.findings-acl.1236/},
year = {2026},
}
MTEB(pol, v1)¶
Polish text embedding quality across classification, clustering, pair classification, retrieval, and semantic similarity, combining adapted community datasets with a novel Polish scientific literature corpus (PLSC).
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| AllegroReviews | Classification | text | pol |
| CBD | Classification | text | pol |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MassiveScenarioClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| PolEmo2.0-IN | Classification | text | pol |
| PolEmo2.0-OUT | Classification | text | pol |
| PAC | Classification | text | pol |
| EightTagsClustering | Clustering | text | pol |
| PlscClusteringS2S | Clustering | text | pol |
| PlscClusteringP2P | Clustering | text | pol |
| CDSC-E | PairClassification | text | pol |
| PpcPC | PairClassification | text | pol |
| PSC | PairClassification | text | pol |
| SICK-E-PL | PairClassification | text | pol |
| CDSC-R | STS | text | pol |
| SICK-R-PL | STS | text | pol |
| STS22 | STS | text | ara, cmn, deu, eng, fra, ... (10) |
Citation
@inproceedings{poswiata2024plmteb,
address = {San Diego, California, United States},
author = {Po{\'s}wiata, Rafa{\l} and Dadas, S{\l}awomir and Pere{\l}kiewicz, Micha{\l} Wiktor},
booktitle = {Findings of the {A}ssociation for {C}omputational {L}inguistics: {ACL} 2026},
doi = {10.18653/v1/2026.findings-acl.1773},
editor = {Liakata, Maria and Moreira, Viviane P. and Zhang, Jiajun and Jurgens, David},
isbn = {979-8-89176-395-1},
month = {jul},
pages = {35601--35619},
publisher = {Association for Computational Linguistics},
title = {{PL}-{MTEB}: {P}olish Massive Text Embedding Benchmark},
url = {https://aclanthology.org/2026.findings-acl.1773/},
year = {2026},
}
MTEB(por, v1)¶
Portuguese text embedding quality benchmark across semantic text similarity, classification, reranking and retrieval.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| Assin2STS | STS | text | por |
| SICK-BR-STS | STS | text | por |
| STSBenchmarkMultilingualSTS | STS | text | cmn, deu, eng, fra, ita, ... (10) |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| BrazilianToxicTweetsClassification | MultilabelClassification | text | por |
| HateSpeechPortugueseClassification | Classification | text | por |
| MultiLongDocReranking | Reranking | text | ara, deu, eng, fra, hin, ... (13) |
| WikipediaRerankingMultilingual | Reranking | text | ben, bul, ces, dan, deu, ... (18) |
| XGlueWPRReranking | Reranking | text | deu, eng, fra, ita, por, ... (7) |
| MultiLongDocRetrieval | Retrieval | text | ara, cmn, deu, eng, fra, ... (13) |
| WikipediaRetrievalMultilingual | Retrieval | text | ben, bul, ces, dan, deu, ... (16) |
| MultiHateClassification | Classification | text | ara, cmn, deu, eng, fra, ... (11) |
| TweetSentimentClassification | Classification | text | ara, deu, eng, fra, hin, ... (8) |
| WebFAQRetrieval | Retrieval | text | ara, aze, ben, bul, cat, ... (51) |
Citation
@inbook{okamura2026multilingualaveragesmtebptbenchmark,
author = {Okamura, Lucas Hideki Takeuchi and Alcoforado, Alexandre and Costa, Anna Helena Reali},
booktitle = {Intelligent Systems},
doi = {10.1007/978-3-032-39892-5_33},
isbn = {9783032398925},
issn = {1611-3349},
month = {Oct},
pages = {501–516},
publisher = {Springer Nature Switzerland},
title = {Beyond Multilingual Averages: MTEB-PT, a Benchmark for Portuguese Sentence Encoders},
url = {https://doi.org/10.1007/978-3-032-39892-5_33},
year = {2026},
}
MTEB(rus, v1)¶
Russian text embedding quality across classification, clustering, reranking, pair classification, retrieval, and semantic similarity, including novel Russian-specific tasks in each category.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| GeoreviewClassification | Classification | text | rus |
| HeadlineClassification | Classification | text | rus |
| InappropriatenessClassification | Classification | text | rus |
| KinopoiskClassification | Classification | text | rus |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MassiveScenarioClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| RuReviewsClassification | Classification | text | rus |
| RuSciBenchGRNTIClassification | Classification | text | rus |
| RuSciBenchOECDClassification | Classification | text | rus |
| GeoreviewClusteringP2P | Clustering | text | rus |
| RuSciBenchGRNTIClusteringP2P | Clustering | text | rus |
| RuSciBenchOECDClusteringP2P | Clustering | text | rus |
| CEDRClassification | MultilabelClassification | text | rus |
| SensitiveTopicsClassification | MultilabelClassification | text | rus |
| TERRa | PairClassification | text | rus |
| MIRACLReranking | Reranking | text | ara, ben, deu, eng, fas, ... (18) |
| RuBQReranking | Reranking | text | rus |
| MIRACLRetrieval | Retrieval | text | ara, ben, deu, eng, fas, ... (18) |
| RiaNewsRetrieval | Retrieval | text | rus |
| RuBQRetrieval | Retrieval | text | rus |
| RUParaPhraserSTS | STS | text | rus |
| STS22 | STS | text | ara, cmn, deu, eng, fra, ... (10) |
| RuSTSBenchmarkSTS | STS | text | rus |
Citation
@inproceedings{snegirev2024russianfocusedembeddersexplorationrumteb,
address = {Albuquerque, New Mexico},
author = {Snegirev, Artem and Tikhonova, Maria and Anna, Maksimova and Fenogenova, Alena and Abramov, Aleksandr},
booktitle = {Proceedings of the 2025 Conference of the Nations of the {A}mericas Chapter of the {A}ssociation for {C}omputational {L}inguistics: Human Language Technologies (Volume 1: Long Papers)},
doi = {10.18653/v1/2025.naacl-long.12},
editor = {Chiruzzo, Luis and Ritter, Alan and Wang, Lu},
isbn = {979-8-89176-189-6},
month = {apr},
pages = {236--254},
publisher = {Association for Computational Linguistics},
title = {The {R}ussian-focused embedders' exploration: ru{MTEB} benchmark and {R}ussian embedding model design},
url = {https://aclanthology.org/2025.naacl-long.12/},
year = {2025},
}
MTEB(rus, v1.1)¶
Russian text embedding quality across classification, clustering, reranking, pair classification, retrieval, and semantic similarity. In v1.1, MIRACLRetrieval and RiaNewsRetrieval were replaced with their HardNegatives variants (v2), which include improved default prompts.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| GeoreviewClassification | Classification | text | rus |
| HeadlineClassification | Classification | text | rus |
| InappropriatenessClassification | Classification | text | rus |
| KinopoiskClassification | Classification | text | rus |
| MassiveIntentClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| MassiveScenarioClassification | Classification | text | afr, amh, ara, aze, ben, ... (50) |
| RuReviewsClassification | Classification | text | rus |
| RuSciBenchGRNTIClassification | Classification | text | rus |
| RuSciBenchOECDClassification | Classification | text | rus |
| GeoreviewClusteringP2P | Clustering | text | rus |
| RuSciBenchGRNTIClusteringP2P | Clustering | text | rus |
| RuSciBenchOECDClusteringP2P | Clustering | text | rus |
| CEDRClassification | MultilabelClassification | text | rus |
| SensitiveTopicsClassification | MultilabelClassification | text | rus |
| TERRa | PairClassification | text | rus |
| MIRACLReranking | Reranking | text | ara, ben, deu, eng, fas, ... (18) |
| RuBQReranking | Reranking | text | rus |
| MIRACLRetrievalHardNegatives.v2 | Retrieval | text | ara, ben, deu, eng, fas, ... (18) |
| RiaNewsRetrievalHardNegatives.v2 | Retrieval | text | rus |
| RuBQRetrieval | Retrieval | text | rus |
| RUParaPhraserSTS | STS | text | rus |
| STS22 | STS | text | ara, cmn, deu, eng, fra, ... (10) |
| RuSTSBenchmarkSTS | STS | text | rus |
Citation
@inproceedings{snegirev2024russianfocusedembeddersexplorationrumteb,
address = {Albuquerque, New Mexico},
author = {Snegirev, Artem and Tikhonova, Maria and Anna, Maksimova and Fenogenova, Alena and Abramov, Aleksandr},
booktitle = {Proceedings of the 2025 Conference of the Nations of the {A}mericas Chapter of the {A}ssociation for {C}omputational {L}inguistics: Human Language Technologies (Volume 1: Long Papers)},
doi = {10.18653/v1/2025.naacl-long.12},
editor = {Chiruzzo, Luis and Ritter, Alan and Wang, Lu},
isbn = {979-8-89176-189-6},
month = {apr},
pages = {236--254},
publisher = {Association for Computational Linguistics},
title = {The {R}ussian-focused embedders' exploration: ru{MTEB} benchmark and {R}ussian embedding model design},
url = {https://aclanthology.org/2025.naacl-long.12/},
year = {2025},
}
MTEB(slk, v1)¶
Slovak Massive Text Embedding Benchmark (SkMTEB), the first comprehensive benchmark for text embeddings in Slovak, a low-resource West Slavic language. SkMTEB consists of 31 tasks across 7 task types, with tasks adapted from both existing and novel resources.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| BelebeleRetrieval | Retrieval | text | acm, afr, als, amh, apc, ... (115) |
| SlovakSumRetrieval | Retrieval | text | slk |
| SMESumRetrieval | Retrieval | text | slk |
| SKQuadRetrieval | Retrieval | text | slk |
| WebFAQRetrieval | Retrieval | text | ara, aze, ben, bul, cat, ... (51) |
| SlovakSTS | STS | text | slk |
| SlovakSumSTS | STS | text | slk |
| SlovakNLI | PairClassification | text | slk |
| SlovakRTE | PairClassification | text | slk |
| DemagogSKNLI | PairClassification | text | slk |
| SlovakHateSpeechClassification.v2 | Classification | text | slk |
| SlovakMovieReviewSentimentClassification.v2 | Classification | text | slk |
| SIB200Classification | Classification | text | ace, acm, acq, aeb, afr, ... (197) |
| MultilingualSentimentClassification | Classification | text | ara, bam, bul, cmn, cym, ... (31) |
| SlovakParlaSentClassification | Classification | text | slk |
| MultiEupSlovakPartyClassification | Classification | text | slk |
| MultiEupSlovakGenderClassification | Classification | text | slk |
| SkQuadReranking | Reranking | text | slk |
| SlovakPharmacyDrMaxReranking | Reranking | text | slk |
| SlovakPharmacyMojaLekarenReranking | Reranking | text | slk |
| SIB200ClusteringS2S | Clustering | text | ace, acm, acq, aeb, afr, ... (197) |
| PravdaSKTagClustering | Clustering | text | slk |
| PravdaSKURLClustering | Clustering | text | slk |
| SlovakSumURLClustering | Clustering | text | slk |
| SMESumCategoryClustering | Clustering | text | slk |
| OpusSlovakEnglishBitextMining | BitextMining | text | slk |
| Tatoeba | BitextMining | text | afr, amh, ang, ara, arq, ... (113) |
| FloresBitextMining | BitextMining | text | ace, acm, acq, aeb, afr, ... (196) |
| NTREXBitextMining | BitextMining | text | afr, amh, arb, aze, bak, ... (119) |
| WebFAQBitextMiningQuestions | BitextMining | text | ara, aze, ben, bul, cat, ... (49) |
| WebFAQBitextMiningQAs | BitextMining | text | ara, aze, ben, bul, cat, ... (49) |
Citation
@inproceedings{suppa2026skmteb,
address = {San Diego, California, United States},
author = {Suppa, Marek and Ridzik, Andrej and Hl{\'a}dek, Daniel and K{\v{n}}a{\v{z}}ekov{\'a}, Nat{\'a}lia and Ondrejov{\'a}, Vikt{\'o}ria},
booktitle = {Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)},
doi = {10.18653/v1/2026.acl-long.2114},
editor = {Liakata, Maria and Moreira, Viviane P. and Zhang, Jiajun and Jurgens, David},
isbn = {979-8-89176-390-6},
month = {jul},
pages = {45597--45628},
publisher = {Association for Computational Linguistics},
title = {{S}k{MTEB}: {S}lovak Massive Text Embedding Benchmark and Model Adaptation},
url = {https://aclanthology.org/2026.acl-long.2114/},
year = {2026},
}
MTEB(spa, v1)¶
Spanish text embedding quality across classification, clustering, pair classification, reranking, retrieval, and semantic similarity. For discussion on benchmark construction, see the original submission.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| SpanishNewsClassification.v2 | Classification | text | spa |
| SpanishSentimentClassification.v2 | Classification | text | spa |
| MLSUMClusteringP2P | Clustering | text | deu, fra, rus, spa |
| MLSUMClusteringS2S | Clustering | text | deu, fra, rus, spa |
| PawsXPairClassification | PairClassification | text | cmn, deu, eng, fra, jpn, ... (7) |
| XNLI | PairClassification | text | ara, bul, deu, ell, eng, ... (14) |
| MIRACLReranking | Reranking | text | ara, ben, deu, eng, fas, ... (18) |
| MIRACLRetrievalHardNegatives.v2 | Retrieval | text | ara, ben, deu, eng, fas, ... (18) |
| MintakaRetrieval | Retrieval | text | ara, deu, fra, hin, ita, ... (8) |
| SpanishPassageRetrievalS2P | Retrieval | text | spa |
| SpanishPassageRetrievalS2S | Retrieval | text | spa |
| XPQARetrieval | Retrieval | text | ara, cmn, deu, eng, fra, ... (13) |
| STSES | STS | text | spa |
| STSBenchmarkMultilingualSTS | STS | text | cmn, deu, eng, fra, ita, ... (10) |
| STS17 | STS | text | ara, deu, eng, fra, ita, ... (9) |
| STS22 | STS | text | ara, cmn, deu, eng, fra, ... (10) |
MTEB(tha, v1)¶
Thai text embedding quality across classification, clustering, pair classification, reranking, and retrieval. Tasks are native Thai or high-quality human translations; machine-translated and cross-lingual tasks are excluded.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| MTOPDomainClassification | Classification | text | deu, eng, fra, hin, spa, ... (6) |
| MTOPIntentClassification | Classification | text | deu, eng, fra, hin, spa, ... (6) |
| SIB200Classification | Classification | text | ace, acm, acq, aeb, afr, ... (197) |
| WisesightSentimentClassification.v2 | Classification | text | tha |
| SIB200ClusteringS2S | Clustering | text | ace, acm, acq, aeb, afr, ... (197) |
| XNLI | PairClassification | text | ara, bul, deu, ell, eng, ... (14) |
| MIRACLReranking | Reranking | text | ara, ben, deu, eng, fas, ... (18) |
| MultiLongDocReranking | Reranking | text | ara, deu, eng, fra, hin, ... (13) |
| BelebeleRetrieval | Retrieval | text | acm, afr, als, amh, apc, ... (115) |
| MIRACLRetrievalHardNegatives.v2 | Retrieval | text | ara, ben, deu, eng, fas, ... (18) |
| MKQARetrieval | Retrieval | text | ara, dan, deu, eng, fin, ... (26) |
| MrTidyRetrieval | Retrieval | text | ara, ben, eng, fin, ind, ... (11) |
| MultiLongDocRetrieval | Retrieval | text | ara, cmn, deu, eng, fra, ... (13) |
| WebFAQRetrieval | Retrieval | text | ara, aze, ben, bul, cat, ... (51) |
| XQuADRetrieval | Retrieval | text | arb, deu, ell, eng, hin, ... (12) |
MVEB(text, video, v1)¶
Text and video embedding quality across retrieval, classification, clustering, pair classification, zero-shot classification, and video-centric QA, for models without an audio encoder.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| AVMemeExamT2VRetrieval | Any2AnyRetrieval | text, video | eng |
| ActivityNetCaptionsT2VRetrieval | Any2AnyRetrieval | video, text | eng |
| AudioCapsAVT2VRetrieval | Any2AnyRetrieval | text, video | eng |
| DiDeMoV2TRetrieval | Any2AnyRetrieval | video, text | eng |
| MSVDV2TRetrieval | Any2AnyRetrieval | video, text | eng |
| Panda70MT2VRetrieval | Any2AnyRetrieval | text, video | eng |
| VALOR32KT2VRetrieval | Any2AnyRetrieval | text, video | eng |
| VATEXT2VRetrieval | Any2AnyRetrieval | text, video | eng |
| OmniVideoBenchVideoCentricQA | VideoCentricQA | video, text | eng |
| AVMemeVideoClassification | VideoClassification | video | bos, bre, deu, eng, fas, ... (16) |
| BreakfastClassification | VideoClassification | video | eng |
| Kinetics700V | VideoClassification | video | eng |
| VGGSoundV | VideoClassification | video | eng |
| RAVDESSVideoClustering | VideoClustering | video | eng |
| HumanAnimalCartoonVPairClassification | VideoPairClassification | video | eng |
| Kinetics400ZeroShot | VideoZeroshotClassification | video, text | eng |
| MELDVideoZeroShot | VideoZeroshotClassification | video, text | eng |
| UCF101VideoZeroShotClassification | VideoZeroshotClassification | video, text | eng |
| WorldSenseVideoZeroShot | VideoZeroshotClassification | video, text | eng |
Citation
@inproceedings{anonymous2026mveb,
author = {Adnan El Assadi and Roman Solomatin and Isaac Chung and Chenghao Xiao and Deep Shah and Shriya Sudhakar and Ayush Sunil Munot and M{\'a}rton Kardos and Niklas Muennighoff and Kenneth Enevoldsen},
booktitle = {The 2026 Conference on Empirical Methods in Natural Language Processing},
title = {{MVEB}: Massive Video Embedding Benchmark},
url = {https://openreview.net/forum?id=p5KyLtjRPo},
year = {2026},
}
MVEB(v1)¶
Audio-visual video embedding quality across retrieval, classification, clustering, pair classification, zero-shot classification, and video-centric QA, with tasks selected to maximize coverage of audio-video joint modality inputs.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| AVMemeExamAT2VRetrieval | Any2AnyRetrieval | audio, text, video | eng |
| ActivityNetCaptionsT2VRetrieval | Any2AnyRetrieval | video, text | eng |
| AudioCapsAVVA2TRetrieval | Any2AnyRetrieval | audio, video, text | eng |
| AudioCapsAVVT2ARetrieval | Any2AnyRetrieval | video, text, audio | eng |
| MSVDT2VRetrieval | Any2AnyRetrieval | text, video | eng |
| VALOR32KT2VARetrieval | Any2AnyRetrieval | text, audio, video | eng |
| VATEXV2ARetrieval | Any2AnyRetrieval | video, audio | eng |
| VATEXVA2TRetrieval | Any2AnyRetrieval | audio, video, text | eng |
| VGGSoundAVA2VRetrieval | Any2AnyRetrieval | audio, video | eng |
| YouCook2T2VARetrieval | Any2AnyRetrieval | text, audio, video | eng |
| EgoSchemaVideoCentricQA | VideoCentricQA | video, text | eng |
| AVEDatasetClassification | VideoClassification | video, audio | eng |
| AVMemeAudioVideoClassification | VideoClassification | video, audio | bos, bre, deu, eng, fas, ... (16) |
| BreakfastClassification | VideoClassification | video | eng |
| Kinetics700VA | VideoClassification | video, audio | eng |
| RAVDESSAVClassification | VideoClassification | video, audio | eng |
| UCF101VideoAudioClassification | VideoClassification | video, audio | eng |
| MELDEmotionAudioVideoClustering | VideoClustering | video, audio | eng |
| MusicAVQACLSAudioVideoClustering | VideoClustering | video, audio | eng |
| HumanAnimalCartoonVAPairClassification | VideoPairClassification | video, audio | eng |
| MusicAVQAVAPairClassification | VideoPairClassification | video, audio | eng |
| HMDB51ZeroShot | VideoZeroshotClassification | video, text | eng |
| WorldSenseAudioVideoZeroShot | VideoZeroshotClassification | video, audio, text | eng |
Citation
@inproceedings{anonymous2026mveb,
author = {Adnan El Assadi and Roman Solomatin and Isaac Chung and Chenghao Xiao and Deep Shah and Shriya Sudhakar and Ayush Sunil Munot and M{\'a}rton Kardos and Niklas Muennighoff and Kenneth Enevoldsen},
booktitle = {The 2026 Conference on Empirical Methods in Natural Language Processing},
title = {{MVEB}: Massive Video Embedding Benchmark},
url = {https://openreview.net/forum?id=p5KyLtjRPo},
year = {2026},
}
MVEB(video, v1)¶
Video-only embedding quality across classification and pair classification, for encoders without a text component. Retrieval, QA, and zero-shot tasks are excluded as they require a text encoder.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| AVMemeVideoClassification | VideoClassification | video | bos, bre, deu, eng, fas, ... (16) |
| BreakfastClassification | VideoClassification | video | eng |
| HMDB51Classification | VideoClassification | video | eng |
| Kinetics600V | VideoClassification | video | eng |
| MELDVideoClassification | VideoClassification | video | eng |
| WorldSenseVideoClassification | VideoClassification | video | eng |
| HumanAnimalCartoonVPairClassification | VideoPairClassification | video | eng |
| MusicAVQAVPairClassification | VideoPairClassification | video | eng |
| RAVDESSAVVPairClassification | VideoPairClassification | video | eng |
Citation
@inproceedings{anonymous2026mveb,
author = {Adnan El Assadi and Roman Solomatin and Isaac Chung and Chenghao Xiao and Deep Shah and Shriya Sudhakar and Ayush Sunil Munot and M{\'a}rton Kardos and Niklas Muennighoff and Kenneth Enevoldsen},
booktitle = {The 2026 Conference on Empirical Methods in Natural Language Processing},
title = {{MVEB}: Massive Video Embedding Benchmark},
url = {https://openreview.net/forum?id=p5KyLtjRPo},
year = {2026},
}
NanoBEIR¶
Zero-shot retrieval quality using subsets of the BEIR datasets, designed for faster evaluation with reduced computational cost.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| NanoArguAnaRetrieval | Retrieval | text | eng |
| NanoClimateFeverRetrieval | Retrieval | text | eng |
| NanoDBPediaRetrieval | Retrieval | text | eng |
| NanoFEVERRetrieval | Retrieval | text | eng |
| NanoFiQA2018Retrieval | Retrieval | text | eng |
| NanoHotpotQARetrieval | Retrieval | text | eng |
| NanoMSMARCORetrieval | Retrieval | text | eng |
| NanoNFCorpusRetrieval | Retrieval | text | eng |
| NanoNQRetrieval | Retrieval | text | eng |
| NanoQuoraRetrieval | Retrieval | text | eng |
| NanoSCIDOCSRetrieval | Retrieval | text | eng |
| NanoSciFactRetrieval | Retrieval | text | eng |
| NanoTouche2020Retrieval | Retrieval | text | eng |
NanoBEIR-multilingual¶
A translated benchmark targeting zero-shot retrieval quality using translated subsets of the BEIR datasets, designed for faster evaluation during training with reduced computational cost.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| MultilingualNanoArguAnaRetrieval | Retrieval | text | ara, deu, eng, fra, ita, ... (11) |
| MultilingualNanoClimateFeverRetrieval | Retrieval | text | ara, deu, eng, fra, ita, ... (11) |
| MultilingualNanoDBPediaRetrieval | Retrieval | text | ara, deu, eng, fra, ita, ... (11) |
| MultilingualNanoFEVERRetrieval | Retrieval | text | ara, deu, eng, fra, ita, ... (11) |
| MultilingualNanoFiQA2018Retrieval | Retrieval | text | ara, deu, eng, fra, ita, ... (11) |
| MultilingualNanoHotpotQARetrieval | Retrieval | text | ara, deu, eng, fra, ita, ... (11) |
| MultilingualNanoMSMARCORetrieval | Retrieval | text | ara, deu, eng, fra, ita, ... (11) |
| MultilingualNanoNFCorpusRetrieval | Retrieval | text | ara, deu, eng, fra, ita, ... (11) |
| MultilingualNanoNQRetrieval | Retrieval | text | ara, deu, eng, fra, ita, ... (11) |
| MultilingualNanoQuoraRetrieval | Retrieval | text | ara, deu, eng, fra, ita, ... (11) |
| MultilingualNanoSCIDOCSRetrieval | Retrieval | text | ara, deu, eng, fra, ita, ... (11) |
| MultilingualNanoSciFactRetrieval | Retrieval | text | ara, deu, eng, fra, ita, ... (11) |
| MultilingualNanoTouche2020Retrieval | Retrieval | text | ara, deu, eng, fra, ita, ... (11) |
R2MED¶
Reasoning-driven medical retrieval quality across biology, bioinformatics, medical sciences, clinical, and treatment scenarios, requiring models to perform multi-step reasoning over medical literature.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| R2MEDBiologyRetrieval | Retrieval | text | eng |
| R2MEDBioinformaticsRetrieval | Retrieval | text | eng |
| R2MEDMedicalSciencesRetrieval | Retrieval | text | eng |
| R2MEDMedXpertQAExamRetrieval | Retrieval | text | eng |
| R2MEDMedQADiagRetrieval | Retrieval | text | eng |
| R2MEDPMCTreatmentRetrieval | Retrieval | text | eng |
| R2MEDPMCClinicalRetrieval | Retrieval | text | eng |
| R2MEDIIYiClinicalRetrieval | Retrieval | text | eng |
Citation
@misc{zhang2026r2medbenchmarkreasoningdrivenmedical,
archiveprefix = {arXiv},
author = {Xiangxu Zhang and Lei Li and Xiao Zhou and Zheng Liu},
eprint = {2505.14558},
primaryclass = {cs.IR},
title = {R2MED: A Benchmark for Reasoning-Driven Medical Retrieval},
url = {https://arxiv.org/abs/2505.14558},
year = {2026},
}
RAR-b¶
Reasoning capabilities of retrieval models, framing commonsense, temporal, and domain-specific reasoning tasks as retrieval problems.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| ARCChallenge | Retrieval | text | eng |
| AlphaNLI | Retrieval | text | eng |
| HellaSwag | Retrieval | text | eng |
| WinoGrande | Retrieval | text | eng |
| PIQA | Retrieval | text | eng |
| SIQA | Retrieval | text | eng |
| Quail | Retrieval | text | eng |
| SpartQA | Retrieval | text | eng |
| TempReasonL1 | Retrieval | text | eng |
| TempReasonL2Pure | Retrieval | text | eng |
| TempReasonL2Fact | Retrieval | text | eng |
| TempReasonL2Context | Retrieval | text | eng |
| TempReasonL3Pure | Retrieval | text | eng |
| TempReasonL3Fact | Retrieval | text | eng |
| TempReasonL3Context | Retrieval | text | eng |
| RARbCode | Retrieval | text | eng |
| RARbMath | Retrieval | text | eng |
Citation
@article{xiao2024rar,
author = {Xiao, Chenghao and Hudson, G Thomas and Al Moubayed, Noura},
journal = {arXiv preprint arXiv:2404.06347},
title = {RAR-b: Reasoning as Retrieval Benchmark},
year = {2024},
}
RTEB(Code, beta)¶
Retrieval quality in the code domain across algorithmic problems, data science tasks, code evaluation, SQL retrieval, and multilingual code retrieval, with tasks representative of real-world production retrieval demands. A domain-specific subset of RTEB. Includes both open and closed datasets; to submit results on private tasks, please open an issue.
Note: We have temporarily removed the 'Private' column to read more about this decision out the announcement.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| AppsRetrieval | Retrieval | text | eng, python |
| DS1000Retrieval | Retrieval | text | eng, python |
| HumanEvalRetrieval | Retrieval | text | eng, python |
| MBPPRetrieval | Retrieval | text | eng, python |
| WikiSQLRetrieval | Retrieval | text | eng, sql |
| FreshStackRetrieval | Retrieval | text | eng, go, javascript, python |
| SWEbenchCodeRetrieval | Retrieval | text | eng, python |
| Code1Retrieval | Retrieval | text | eng |
| JapaneseCode1Retrieval | Retrieval | text | jpn |
RTEB(Health, beta)¶
Retrieval quality in the healthcare and medical domain across medical Q&A, healthcare information retrieval, and multilingual medical consultation, with tasks representative of real-world production retrieval demands. A domain-specific subset of RTEB. Includes both open and closed datasets; to submit results on private tasks, please open an issue.
Note: We have temporarily removed the 'Private' column to read more about this decision out the announcement.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| ChatDoctorRetrieval | Retrieval | text | eng |
| CUREv1 | Retrieval | text | eng, fra, spa |
| EnglishHealthcare1Retrieval | Retrieval | text | eng |
| GermanHealthcare1Retrieval | Retrieval | text | deu |
RTEB(Law, beta)¶
Retrieval quality in the legal domain across case documents, statutes, legal summarization, and multilingual legal Q&A, with tasks representative of real-world production retrieval demands. A domain-specific subset of RTEB. Includes both open and closed datasets; to submit results on private tasks, please open an issue.
Note: We have temporarily removed the 'Private' column to read more about this decision out the announcement.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| AILACasedocs | Retrieval | text | eng |
| AILAStatutes | Retrieval | text | eng |
| LegalSummarization | Retrieval | text | eng |
| LegalQuAD | Retrieval | text | deu |
| FrenchLegal1Retrieval | Retrieval | text | fra |
| GermanLegal1Retrieval | Retrieval | text | deu |
| JapaneseLegal1Retrieval | Retrieval | text | jpn |
RTEB(beta)¶
Retrieval quality across specialized domains including legal, finance, code, and healthcare in multiple languages, with tasks representative of real-world production retrieval demands. Includes both open and closed datasets; to submit results on private tasks, please open an issue.
Note: We have temporarily removed the 'Private' column to read more about this decision out the announcement.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| AILACasedocs | Retrieval | text | eng |
| AILAStatutes | Retrieval | text | eng |
| LegalSummarization | Retrieval | text | eng |
| LegalQuAD | Retrieval | text | deu |
| FinanceBenchRetrieval | Retrieval | text | eng |
| HC3FinanceRetrieval | Retrieval | text | eng |
| FinQARetrieval | Retrieval | text | eng |
| AppsRetrieval | Retrieval | text | eng, python |
| DS1000Retrieval | Retrieval | text | eng, python |
| HumanEvalRetrieval | Retrieval | text | eng, python |
| MBPPRetrieval | Retrieval | text | eng, python |
| WikiSQLRetrieval | Retrieval | text | eng, sql |
| FreshStackRetrieval | Retrieval | text | eng, go, javascript, python |
| SWEbenchCodeRetrieval | Retrieval | text | eng, python |
| ChatDoctorRetrieval | Retrieval | text | eng |
| CUREv1 | Retrieval | text | eng, fra, spa |
| MIRACLRetrievalHardNegatives | Retrieval | text | ara, ben, deu, eng, fas, ... (18) |
| Code1Retrieval | Retrieval | text | eng |
| JapaneseCode1Retrieval | Retrieval | text | jpn |
| EnglishFinance1Retrieval | Retrieval | text | eng |
| EnglishFinance2Retrieval | Retrieval | text | eng |
| EnglishFinance3Retrieval | Retrieval | text | eng |
| EnglishFinance4Retrieval | Retrieval | text | eng |
| EnglishHealthcare1Retrieval | Retrieval | text | eng |
| French1Retrieval | Retrieval | text | fra |
| FrenchLegal1Retrieval | Retrieval | text | fra |
| German1Retrieval | Retrieval | text | deu |
| GermanHealthcare1Retrieval | Retrieval | text | deu |
| GermanLegal1Retrieval | Retrieval | text | deu |
| JapaneseLegal1Retrieval | Retrieval | text | jpn |
RTEB(deu, beta)¶
Retrieval quality in German across legal, healthcare, and business domains, with tasks representative of real-world production retrieval demands. A German-language subset of RTEB. Includes both open and closed datasets; to submit results on private tasks, please open an issue.
Note: We have temporarily removed the 'Private' column to read more about this decision out the announcement.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| LegalQuAD | Retrieval | text | deu |
| German1Retrieval | Retrieval | text | deu |
| GermanHealthcare1Retrieval | Retrieval | text | deu |
| GermanLegal1Retrieval | Retrieval | text | deu |
RTEB(eng, beta)¶
Retrieval quality in English across legal, finance, code, and healthcare domains, with tasks representative of real-world production retrieval demands. An English-only subset of RTEB. Includes both open and closed datasets; to submit results on private tasks, please open an issue.
Note: We have temporarily removed the 'Private' column to read more about this decision out the announcement.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| AILACasedocs | Retrieval | text | eng |
| AILAStatutes | Retrieval | text | eng |
| LegalSummarization | Retrieval | text | eng |
| FinanceBenchRetrieval | Retrieval | text | eng |
| HC3FinanceRetrieval | Retrieval | text | eng |
| FinQARetrieval | Retrieval | text | eng |
| AppsRetrieval | Retrieval | text | eng, python |
| DS1000Retrieval | Retrieval | text | eng, python |
| HumanEvalRetrieval | Retrieval | text | eng, python |
| MBPPRetrieval | Retrieval | text | eng, python |
| WikiSQLRetrieval | Retrieval | text | eng, sql |
| FreshStackRetrieval | Retrieval | text | eng, go, javascript, python |
| SWEbenchCodeRetrieval | Retrieval | text | eng, python |
| ChatDoctorRetrieval | Retrieval | text | eng |
| Code1Retrieval | Retrieval | text | eng |
| EnglishFinance1Retrieval | Retrieval | text | eng |
| EnglishFinance2Retrieval | Retrieval | text | eng |
| EnglishFinance3Retrieval | Retrieval | text | eng |
| EnglishFinance4Retrieval | Retrieval | text | eng |
| EnglishHealthcare1Retrieval | Retrieval | text | eng |
| CUREv1 | Retrieval | text | eng, fra, spa |
RTEB(fin, beta)¶
Retrieval quality in the financial domain across finance benchmarks, Q&A, financial document retrieval, and corporate governance, with tasks representative of real-world production retrieval demands. A domain-specific subset of RTEB. Includes both open and closed datasets; to submit results on private tasks, please open an issue.
Note: We have temporarily removed the 'Private' column to read more about this decision out the announcement.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| FinanceBenchRetrieval | Retrieval | text | eng |
| HC3FinanceRetrieval | Retrieval | text | eng |
| FinQARetrieval | Retrieval | text | eng |
| EnglishFinance1Retrieval | Retrieval | text | eng |
| EnglishFinance2Retrieval | Retrieval | text | eng |
| EnglishFinance3Retrieval | Retrieval | text | eng |
| EnglishFinance4Retrieval | Retrieval | text | eng |
RTEB(fra, beta)¶
Retrieval quality in French across legal and general knowledge domains, with tasks representative of real-world production retrieval demands. A French-language subset of RTEB. Includes both open and closed datasets; to submit results on private tasks, please open an issue.
Note: We have temporarily removed the 'Private' column to read more about this decision out the announcement.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| CUREv1 | Retrieval | text | eng, fra, spa |
| French1Retrieval | Retrieval | text | fra |
| FrenchLegal1Retrieval | Retrieval | text | fra |
RTEB(jpn, beta)¶
Retrieval quality in Japanese across legal and code domains, with tasks representative of real-world production retrieval demands. A Japanese-language subset of RTEB. Includes both open and closed datasets; to submit results on private tasks, please open an issue.
Note: We have temporarily removed the 'Private' column to read more about this decision out the announcement.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| JapaneseCode1Retrieval | Retrieval | text | jpn |
| JapaneseLegal1Retrieval | Retrieval | text | jpn |
RuSciBench¶
Scientific text embedding quality in Russian and English across bitext mining, classification, retrieval, and regression tasks, using data sourced from eLibrary, Russia's largest electronic library of scientific publications.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| RuSciBenchBitextMining.v2 | BitextMining | text | eng, rus |
| RuSciBenchCoreRiscClassification | Classification | text | eng, rus |
| RuSciBenchGRNTIClassification.v2 | Classification | text | eng, rus |
| RuSciBenchOECDClassification.v2 | Classification | text | eng, rus |
| RuSciBenchPubTypeClassification | Classification | text | eng, rus |
| RuSciBenchCiteRetrieval | Retrieval | text | eng, rus |
| RuSciBenchCociteRetrieval | Retrieval | text | eng, rus |
| RuSciBenchCitedCountRegression | Regression | text | eng, rus |
| RuSciBenchYearPublRegression | Regression | text | eng, rus |
Citation
@article{vatolin2024ruscibench,
author = {Vatolin, A. and Gerasimenko, N. and Ianina, A. and Vorontsov, K.},
doi = {10.1134/S1064562424602191},
issn = {1531-8362},
journal = {Doklady Mathematics},
month = {12},
number = {1},
pages = {S251--S260},
title = {RuSciBench: Open Benchmark for Russian and English Scientific Document Representations},
url = {https://doi.org/10.1134/S1064562424602191},
volume = {110},
year = {2024},
}
VN-MTEB (vie, v1)¶
Vietnamese text embedding quality across retrieval, classification, pair classification, clustering, reranking, and semantic similarity.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| ArguAna-VN | Retrieval | text | vie |
| SciFact-VN | Retrieval | text | vie |
| ClimateFEVER-VN | Retrieval | text | vie |
| FEVER-VN | Retrieval | text | vie |
| DBPedia-VN | Retrieval | text | vie |
| NQ-VN | Retrieval | text | vie |
| HotpotQA-VN | Retrieval | text | vie |
| MSMARCO-VN | Retrieval | text | vie |
| TRECCOVID-VN | Retrieval | text | vie |
| FiQA2018-VN | Retrieval | text | vie |
| NFCorpus-VN | Retrieval | text | vie |
| SCIDOCS-VN | Retrieval | text | vie |
| Touche2020-VN | Retrieval | text | vie |
| Quora-VN | Retrieval | text | vie |
| CQADupstackAndroid-VN | Retrieval | text | vie |
| CQADupstackGis-VN | Retrieval | text | vie |
| CQADupstackMathematica-VN | Retrieval | text | vie |
| CQADupstackPhysics-VN | Retrieval | text | vie |
| CQADupstackProgrammers-VN | Retrieval | text | vie |
| CQADupstackStats-VN | Retrieval | text | vie |
| CQADupstackTex-VN | Retrieval | text | vie |
| CQADupstackUnix-VN | Retrieval | text | vie |
| CQADupstackWebmasters-VN | Retrieval | text | vie |
| CQADupstackWordpress-VN | Retrieval | text | vie |
| Banking77VNClassification | Classification | text | vie |
| EmotionVNClassification | Classification | text | vie |
| AmazonCounterfactualVNClassification | Classification | text | vie |
| MTOPDomainVNClassification | Classification | text | vie |
| TweetSentimentExtractionVNClassification | Classification | text | vie |
| ToxicConversationsVNClassification | Classification | text | vie |
| ImdbVNClassification | Classification | text | vie |
| MTOPIntentVNClassification | Classification | text | vie |
| MassiveScenarioVNClassification | Classification | text | vie |
| MassiveIntentVNClassification | Classification | text | vie |
| AmazonReviewsVNClassification | Classification | text | vie |
| AmazonPolarityVNClassification | Classification | text | vie |
| SprintDuplicateQuestions-VN | PairClassification | text | vie |
| TwitterSemEval2015-VN | PairClassification | text | vie |
| TwitterURLCorpus-VN | PairClassification | text | vie |
| TwentyNewsgroupsClustering-VN | Clustering | text | vie |
| RedditClusteringP2P-VN | Clustering | text | vie |
| StackExchangeClusteringP2P-VN | Clustering | text | vie |
| StackExchangeClustering-VN | Clustering | text | vie |
| RedditClustering-VN | Clustering | text | vie |
| SciDocsRR-VN | Reranking | text | vie |
| AskUbuntuDupQuestions-VN | Reranking | text | vie |
| StackOverflowDupQuestions-VN | Reranking | text | vie |
| BIOSSES-VN | STS | text | vie |
| SICK-R-VN | STS | text | vie |
| STSBenchmark-VN | STS | text | vie |
Citation
@inproceedings{pham2025vnmtebvietnamesemassivetext,
address = {Rabat, Morocco},
author = {Pham, Loc and Luu, Tung and Vo, Thu and Nguyen, Minh and Hoang, Viet},
booktitle = {Findings of the {A}ssociation for {C}omputational {L}inguistics: {EACL} 2026},
doi = {10.18653/v1/2026.findings-eacl.86},
editor = {Demberg, Vera and Inui, Kentaro and Marquez, Llu{\'i}s},
isbn = {979-8-89176-386-9},
month = {mar},
pages = {1705--1725},
publisher = {Association for Computational Linguistics},
title = {{VN}-{MTEB}: {V}ietnamese Massive Text Embedding Benchmark},
url = {https://aclanthology.org/2026.findings-eacl.86/},
year = {2026},
}
ViDoRe(v1&v2)¶
Visual document retrieval across diverse document types and domains, combining the ViDoRe v1 and v2 task sets.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| VidoreArxivQARetrieval | DocumentUnderstanding | text, image | eng |
| VidoreDocVQARetrieval | DocumentUnderstanding | text, image | eng |
| VidoreInfoVQARetrieval | DocumentUnderstanding | text, image | eng |
| VidoreTabfquadRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreTatdqaRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreShiftProjectRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreSyntheticDocQAAIRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreSyntheticDocQAEnergyRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreSyntheticDocQAGovernmentReportsRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreSyntheticDocQAHealthcareIndustryRetrieval | DocumentUnderstanding | text, image | eng |
| Vidore2ESGReportsRetrieval | DocumentUnderstanding | text, image | deu, eng, fra, spa |
| Vidore2EconomicsReportsRetrieval | DocumentUnderstanding | text, image | deu, eng, fra, spa |
| Vidore2BioMedicalLecturesRetrieval | DocumentUnderstanding | text, image | deu, eng, fra, spa |
| Vidore2ESGReportsHLRetrieval | DocumentUnderstanding | text, image | eng |
Citation
@article{mace2025vidorev2,
author = {Macé, Quentin and Loison António and Faysse, Manuel},
journal = {arXiv preprint arXiv:2505.17166},
title = {ViDoRe Benchmark V2: Raising the Bar for Visual Retrieval},
year = {2025},
}
ViDoRe(v1)¶
Visual document retrieval across diverse document types and domains, matching natural language queries to document page images.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| VidoreArxivQARetrieval | DocumentUnderstanding | text, image | eng |
| VidoreDocVQARetrieval | DocumentUnderstanding | text, image | eng |
| VidoreInfoVQARetrieval | DocumentUnderstanding | text, image | eng |
| VidoreTabfquadRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreTatdqaRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreShiftProjectRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreSyntheticDocQAAIRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreSyntheticDocQAEnergyRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreSyntheticDocQAGovernmentReportsRetrieval | DocumentUnderstanding | text, image | eng |
| VidoreSyntheticDocQAHealthcareIndustryRetrieval | DocumentUnderstanding | text, image | eng |
Citation
@inproceedings{faysse2024colpali,
archiveprefix = {arXiv},
author = {Manuel Faysse and Hugues Sibille and Tony Wu and Bilel Omrani and Gautier Viaud and CELINE HUDELOT and Pierre Colombo},
booktitle = {The Thirteenth International Conference on Learning Representations},
eprint = {2407.01449},
title = {ColPali: Efficient Document Retrieval with Vision Language Models},
url = {https://openreview.net/forum?id=ogjBpZ8uSi},
year = {2025},
}
ViDoRe(v2)¶
Visual document retrieval across ESG reports, economics reports, biomedical lectures, and related enterprise document types, matching natural language queries to document page images.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| Vidore2ESGReportsRetrieval | DocumentUnderstanding | text, image | deu, eng, fra, spa |
| Vidore2EconomicsReportsRetrieval | DocumentUnderstanding | text, image | deu, eng, fra, spa |
| Vidore2BioMedicalLecturesRetrieval | DocumentUnderstanding | text, image | deu, eng, fra, spa |
| Vidore2ESGReportsHLRetrieval | DocumentUnderstanding | text, image | eng |
Citation
@article{mace2025vidorev2,
author = {Macé, Quentin and Loison António and Faysse, Manuel},
journal = {arXiv preprint arXiv:2505.17166},
title = {ViDoRe Benchmark V2: Raising the Bar for Visual Retrieval},
year = {2025},
}
ViDoRe(v3)¶
Visual document retrieval across multi-modal enterprise documents spanning finance, industrial, computer science, pharmaceutical, and other professional domains. Includes both open and closed datasets; to submit results on private tasks, please open an issue.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| Vidore3FinanceEnRetrieval | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3IndustrialRetrieval | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3ComputerScienceRetrieval | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3PharmaceuticalsRetrieval | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3HrRetrieval | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3FinanceFrRetrieval | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3PhysicsRetrieval | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3EnergyRetrieval | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3TelecomRetrieval | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3NuclearRetrieval | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
Citation
@inproceedings{loison2026vidorev3comprehensiveevaluation,
address = {San Diego, California, United States},
author = {Loison, Ant{\'o}nio and Mac{\'e}, Quentin and Edy, Antoine and Xing, Victor and Balough, Tom and Moreira, Gabriel de Souza P. and Liu, Bo and Faysse, Manuel and Hudelot, Celine and Viaud, Gautier},
booktitle = {Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)},
doi = {10.18653/v1/2026.acl-long.755},
editor = {Liakata, Maria and Moreira, Viviane P. and Zhang, Jiajun and Jurgens, David},
isbn = {979-8-89176-390-6},
month = {jul},
pages = {16570--16600},
publisher = {Association for Computational Linguistics},
title = {{V}i{D}o{R}e {V}3: A Comprehensive Evaluation of Retrieval Augmented Generation in Complex Real-World Scenarios},
url = {https://aclanthology.org/2026.acl-long.755/},
year = {2026},
}
ViDoRe(v3.1)¶
Visual document retrieval across multi-modal enterprise documents spanning finance, industrial, computer science, pharmaceutical, and other professional domains. Includes both open and closed datasets; to submit results on private tasks, please open an issue. v3.1 adds markdown derived from OCR to support text-only and joint image-text baselines.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| Vidore3FinanceEnRetrieval.v2 | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3IndustrialRetrieval.v2 | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3ComputerScienceRetrieval.v2 | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3PharmaceuticalsRetrieval.v2 | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3HrRetrieval.v2 | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3FinanceFrRetrieval.v2 | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3PhysicsRetrieval.v2 | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3EnergyRetrieval.v2 | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3TelecomRetrieval.v2 | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3NuclearRetrieval.v2 | DocumentUnderstanding | text, image | deu, eng, fra, ita, por, ... (6) |
Citation
@inproceedings{loison2026vidorev3comprehensiveevaluation,
address = {San Diego, California, United States},
author = {Loison, Ant{\'o}nio and Mac{\'e}, Quentin and Edy, Antoine and Xing, Victor and Balough, Tom and Moreira, Gabriel de Souza P. and Liu, Bo and Faysse, Manuel and Hudelot, Celine and Viaud, Gautier},
booktitle = {Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)},
doi = {10.18653/v1/2026.acl-long.755},
editor = {Liakata, Maria and Moreira, Viviane P. and Zhang, Jiajun and Jurgens, David},
isbn = {979-8-89176-390-6},
month = {jul},
pages = {16570--16600},
publisher = {Association for Computational Linguistics},
title = {{V}i{D}o{R}e {V}3: A Comprehensive Evaluation of Retrieval Augmented Generation in Complex Real-World Scenarios},
url = {https://aclanthology.org/2026.acl-long.755/},
year = {2026},
}
ViDoRe(v3.1, reranking)¶
Reranking of visual documents on the ViDoRe v3.1 domains. For each domain, the candidates are the top-50 pages retrieved by one of four first-stage retrievers; BM25, bge-m3, Qwen3-VL-Embedding-2B and Nemotron-3.5-Embed-8B, so rerankers are compared on candidate lists from various model types. Includes both open and closed datasets; to submit results on private tasks, please open an issue.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| Vidore3ComputerScienceBM25sReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3EnergyBM25sReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3FinanceEnBM25sReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3FinanceFrBM25sReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3HrBM25sReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3IndustrialBM25sReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3PharmaceuticalsBM25sReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3PhysicsBM25sReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3TelecomBM25sReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3NuclearBM25sReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3ComputerScienceBGEm3Reranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3EnergyBGEm3Reranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3FinanceEnBGEm3Reranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3FinanceFrBGEm3Reranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3HrBGEm3Reranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3IndustrialBGEm3Reranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3PharmaceuticalsBGEm3Reranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3PhysicsBGEm3Reranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3TelecomBGEm3Reranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3NuclearBGEm3Reranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3ComputerScienceQwen3VLEmbedding2BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3EnergyQwen3VLEmbedding2BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3FinanceEnQwen3VLEmbedding2BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3FinanceFrQwen3VLEmbedding2BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3HrQwen3VLEmbedding2BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3IndustrialQwen3VLEmbedding2BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3PharmaceuticalsQwen3VLEmbedding2BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3PhysicsQwen3VLEmbedding2BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3TelecomQwen3VLEmbedding2BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3NuclearQwen3VLEmbedding2BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3ComputerScienceNemotron35Embed8BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3EnergyNemotron35Embed8BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3FinanceEnNemotron35Embed8BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3FinanceFrNemotron35Embed8BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3HrNemotron35Embed8BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3IndustrialNemotron35Embed8BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3PharmaceuticalsNemotron35Embed8BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3PhysicsNemotron35Embed8BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3TelecomNemotron35Embed8BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
| Vidore3NuclearNemotron35Embed8BReranking.v2 | Reranking | text, image | deu, eng, fra, ita, por, ... (6) |
Citation
@inproceedings{loison2026vidorev3comprehensiveevaluation,
address = {San Diego, California, United States},
author = {Loison, Ant{\'o}nio and Mac{\'e}, Quentin and Edy, Antoine and Xing, Victor and Balough, Tom and Moreira, Gabriel de Souza P. and Liu, Bo and Faysse, Manuel and Hudelot, Celine and Viaud, Gautier},
booktitle = {Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)},
doi = {10.18653/v1/2026.acl-long.755},
editor = {Liakata, Maria and Moreira, Viviane P. and Zhang, Jiajun and Jurgens, David},
isbn = {979-8-89176-390-6},
month = {jul},
pages = {16570--16600},
publisher = {Association for Computational Linguistics},
title = {{V}i{D}o{R}e {V}3: A Comprehensive Evaluation of Retrieval Augmented Generation in Complex Real-World Scenarios},
url = {https://aclanthology.org/2026.acl-long.755/},
year = {2026},
}
VisRAG Retrieval(v1)¶
Visual retrieval augmented generation quality across document types including scientific papers, charts, infographics, plots, and multi-page documents.
Tasks
| name | type | modalities | languages |
|---|---|---|---|
| VisRAGRetArxivQA | Retrieval | text, image | eng |
| VisRAGRetChartQA | Retrieval | text, image | eng |
| VisRAGRetInfoVQA | Retrieval | text, image | eng |
| VisRAGRetPlotQA | Retrieval | text, image | eng |
| VisRAGRetMPDocVQA | Retrieval | text, image | eng |
| VisRAGRetSlideVQA | Retrieval | text, image | eng |
Citation
@misc{yu2024visrag,
archiveprefix = {arXiv},
author = {Shi Yu and Chaoyue Tang and Bokai Xu and Junbo Cui and Junhao Ran and Yukun Yan and Zhenghao Liu and Shuo Wang and Xu Han and Zhiyuan Liu and Maosong Sun},
eprint = {2410.10594},
primaryclass = {cs.IR},
title = {VisRAG: Vision-based Retrieval-augmented Generation on Multi-modality Documents},
url = {https://arxiv.org/abs/2410.10594},
year = {2025},
}