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paperswithcode_id
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10.7k
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6ab65a7f909092518dca860f
XiaomiMiMo/MiMo-V2.6-RL-oss
XiaomiMiMo
{"license": "apache-2.0", "configs": [{"config_name": "code", "data_files": "code.parquet"}, {"config_name": "cyber", "data_files": "cyber.parquet"}, {"config_name": "general", "data_files": "general/train.parquet"}, {"config_name": "webdev", "data_files": "webdev.parquet"}, {"config_name": "music", "data_files": "musi...
false
False
2026-09-26T01:40:41
565
552
false
639865fd3374018d6cb29b9fb82dd531406fcf5f
Agentic RL Environments RL training environments for LLM agents. Domain Task Family Verifier Code Software engineering Executable tests Cyber Vulnerability reproduction Rule checks General Knowledge work Rubric-based judging Visual Web development Visual grading Music Symbolic music co...
47,819
47,819
12,102,484,722
[ "license:apache-2.0", "size_categories:1K<n<10K", "format:parquet", "modality:document", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "region:us" ]
2026-09-25T11:26:55
null
null
6aa321e46caea5109a90c179
secemp9/arxiv-complete
secemp9
{"license": "other", "license_name": "mixed-arxiv-author-licenses", "license_link": "LICENSE", "pretty_name": "arXiv Complete Corpus", "language": ["en"], "task_categories": ["text-generation", "text-retrieval"], "tags": ["arxiv", "scientific-papers", "latex", "preprints", "full-text"], "size_categories": ["10M<n<100M"...
false
False
2026-09-19T20:39:46
513
96
false
cee894837962fede5612cccf2a4c7cacf49b4c3a
arXiv Complete Corpus A snapshot of arXiv's metadata, version history, submission files and rendered documents. It covers 3,148,796 papers and includes file contents, paths, sizes and SHA-256 digests. Metadata comes from arXiv's OAI-PMH arXivRaw interface; files come from the GCS mirror, S3 source archiv...
114,683
114,683
16,076,057,281,538
[ "task_categories:text-generation", "task_categories:text-retrieval", "language:en", "license:other", "size_categories:100M<n<1B", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:dask", "library:polars", "library:mlcroissant", "arxiv:2401.18030", "region:...
2026-09-10T21:32:20
null
null
6a981c1f3a639ff95e1342fa
MoreThought/Fable-5.1-Max-Reasoning-Filtered-10000x
MoreThought
{"license": "apache-2.0", "task_categories": ["text-generation", "question-answering"], "language": ["en"], "pretty_name": "The First And Best Fable 5.1 Reasoning Data", "tags": ["fable 5.1", "coding", "synthetic", "thinking", "think", "reason", "reasoning", "distill", "distillation", "agent", "agentic", "SFT", "CoT", ...
false
False
2026-09-24T14:27:20
219
77
false
602d49c99c4af5530cc02327dd2d90827c84292a
Dataset Description This dataset contains 10,000 agentic coding and reasoning multi-turn high-quality traces generated by the new Fable 5.1 model using max reasoning effort. It holds almost 500,000,000 tokens of step-by-step chain-of-thought programming across multiple complex domains. It has also been ...
4,177
4,177
2,594,907,881
[ "task_categories:text-generation", "task_categories:question-answering", "language:en", "license:apache-2.0", "size_categories:10K<n<100K", "format:json", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "region:us", "fable 5.1", "coding", "synthetic", "thin...
2026-09-02T12:52:47
null
null
6ab831e64edba2b438670785
nisten/opus5-5-doctor-patient-conversations-all-human-diseases
nisten
{"license": "apache-2.0", "language": ["en"], "task_categories": ["question-answering", "text-generation"], "tags": ["medical", "healthcare", "clinical", "synthetic", "doctor-patient", "chatml", "rag", "conversational"], "size_categories": ["1K<n<10K"], "pretty_name": "Doctor-Patient Conversations \u2014 All Human Dise...
false
False
2026-09-27T16:02:46
77
77
false
9277244e642a8ba02cb8c1d26408e5792932045b
Opus-5.5 generated Doctor-Patient Conversations for All Human Diseases The sequel to nisten/opus-doctor-patient-conversations-all-human-diseases (Opus 4.8). Same disease list, same 20-key schema, same ChatML conversations — regenerated from scratch with Claude Opus 5.5, one agent per disease, and held to...
577
577
75,466,355
[ "task_categories:question-answering", "task_categories:text-generation", "language:en", "license:apache-2.0", "size_categories:1K<n<10K", "region:us", "medical", "healthcare", "clinical", "synthetic", "doctor-patient", "chatml", "rag", "conversational" ]
2026-09-26T20:58:14
null
null
6a34c6065edc6bacb0b36213
espnet/yodas3
espnet
{"license": "cc-by-3.0", "task_categories": ["audio-to-audio", "automatic-speech-recognition", "text-to-speech", "translation"], "dataset_info": [{"config_name": "preview", "features": [{"name": "audio", "dtype": "audio"}, {"name": "lang", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "shard", "dtype"...
false
False
2026-09-30T08:40:08
77
73
false
b7ce8c5660698c0ec39545fa5db2217213189d1d
YODAS v3 Paper YODAS v3 is a large web-crawled dataset containing over 1.1 million hours of audio that were originally released under a CC-BY-3.0 license. The dataset contains audio in over 100 languages. YODAS v3 can be used for a variety of multi-modal tasks, including Automatic Speech Recognition, Tex...
32,918
32,918
55,601,473,635,770
[ "task_categories:audio-to-audio", "task_categories:automatic-speech-recognition", "task_categories:text-to-speech", "task_categories:translation", "license:cc-by-3.0", "region:us" ]
2026-06-19T04:31:02
null
null
621ffdd236468d709f184284
wikimedia/wikipedia
wikimedia
{"language": ["ab", "ace", "ady", "af", "alt", "am", "ami", "an", "ang", "anp", "ar", "arc", "ary", "arz", "as", "ast", "atj", "av", "avk", "awa", "ay", "az", "azb", "ba", "ban", "bar", "bbc", "bcl", "be", "bg", "bh", "bi", "bjn", "blk", "bm", "bn", "bo", "bpy", "br", "bs", "bug", "bxr", "ca", "cbk", "cdo", "ce", "ceb"...
false
False
2024-01-09T09:40:51
1,599
64
false
b04c8d1ceb2f5cd4588862100d08de323dccfbaa
Dataset Card for Wikimedia Wikipedia Dataset Summary Wikipedia dataset containing cleaned articles of all languages. The dataset is built from the Wikipedia dumps (https://dumps.wikimedia.org/) with one subset per language, each containing a single train split. Each example contains the co...
277,034
3,269,683
71,792,022,791
[ "task_categories:text-generation", "task_categories:fill-mask", "task_ids:language-modeling", "task_ids:masked-language-modeling", "language:ab", "language:ace", "language:ady", "language:af", "language:alt", "language:am", "language:ami", "language:an", "language:ang", "language:anp", "...
2022-03-02T23:29:22
null
null
6ab4f16cb386daf00b9d61ee
FineEnvs/SmolDataEnvs
FineEnvs
{"license": "mit", "task_categories": ["question-answering", "table-question-answering"], "tags": ["smoldataenvs", "data-analysis", "agent", "rl-environment", "reinforcement-learning", "code-agent"], "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "pat...
false
False
2026-09-30T05:24:11
63
63
false
6c439f075cf550793b1bfd7b887a41e51f3b23ab
📈 SmolDataEnvs 5.5K+ RL tasks for hill-climbing small models in code and data science. A 2B model on these tasks. Left: what it optimises. Right: 144 held-out tasks it never trains on. Two runs over the same 5,000 tasks: shuffled against a curriculum ordered easiest to hardest. Data-anal...
3,375
3,375
4,436,042
[ "task_categories:question-answering", "task_categories:table-question-answering", "license:mit", "size_categories:1K<n<10K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "region:us", "smoldataenvs", "d...
2026-09-24T09:46:20
null
null
6aaa4864f37373a4ce11d91a
LocalLLaMA/typed-decisions
LocalLLaMA
{"license": "apache-2.0", "language": ["en"], "pretty_name": "Typed Decisions", "size_categories": ["n<1K"], "task_categories": ["text-classification"], "tags": ["structured-decisions", "calibration", "probabilistic-classification", "system-one", "workflow-evaluation", "synthetic"], "configs": [{"config_name": "agent_t...
false
False
2026-09-30T03:27:01
73
56
false
e135720c8fdff7896a4e4068cff624a899d41597
Typed Decisions A benchmark for typed probabilistic decisions. A model gets one piece of unstructured state and answers five typed questions about it at once, and every answer is a probability distribution, not a single label. The schema follows the System One primitives (noul, choice, score) used by Typ...
19,901
19,901
2,167,016
[ "task_categories:text-classification", "language:en", "license:apache-2.0", "size_categories:1K<n<10K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "region:us", "structured-decisions", "calibration", ...
2026-09-16T07:42:28
null
null
6aad2d99c1832da6f69ad2e0
Harland/OmniVChat
Harland
{"license": "cc-by-nc-nd-4.0", "task_categories": ["video-text-to-text"], "language": ["en", "zh"], "tags": ["audio-visual", "omni", "benchmark", "rubric", "reinforcement-learning"], "size_categories": ["1K<n<10K"], "configs": [{"config_name": "single_turn", "data_files": "data/single_turn.jsonl"}, {"config_name": "mul...
false
False
2026-09-21T04:52:52
50
45
false
96a77b5cc67f48d52996e7594756d6156681dae6
OmniVChat: Synthesizing, Benchmarking, and Training for Native Audio-Visual Dialogue &nbsp;&nbsp;&nbsp;&nbsp; 1 The Chinese University of Hong Kong 2 Alibaba Token Hub, Alibaba Group 3 Shanghai Jiao Tong University 4 Shanghai Innovation Institute 5 Zhejiang University OmniVChat (Omni Video Chat) is the...
3,632
3,632
29,707,414,986
[ "task_categories:video-text-to-text", "language:en", "language:zh", "license:cc-by-nc-nd-4.0", "size_categories:1K<n<10K", "format:json", "modality:text", "modality:video", "library:datasets", "library:pandas", "library:polars", "library:mlcroissant", "arxiv:2609.21465", "region:us", "au...
2026-09-18T12:24:57
null
null
6a5466cdd7c4631ab9b28b80
genrobot2025/Gen-HumanEgo
genrobot2025
"{\"license\": \"cc-by-sa-4.0\", \"task_categories\": [\"robotics\"], \"language\": [\"en\"], \"tags(...TRUNCATED)
false
auto
2026-09-25T04:29:13
45
40
false
3cca54aeba0d9af3ebf4995b035d23b41f9387da
"\n\t\n\t\t\n\t\n\t\n\t\tGen-HumanEgo\n\t\n\n\n \n\n\n1,800+ hours of egocentric human demonstratio(...TRUNCATED)
266,616
267,079
62,035,012,405,416
["task_categories:robotics","language:en","license:cc-by-sa-4.0","size_categories:n>1T","region:us",(...TRUNCATED)
2026-07-13T04:17:17
null
null
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Changelog

NEW Changes March 11th 2026

  • Added new split: arxiv_papers, sourced from the Hugging Face /api/papers endpoint
  • papers continues to point to daily_papers.parquet, which is the Daily Papers feed

NEW Changes July 25th

  • added baseModels field to models which shows the models that the user tagged as base models for that model

Example:

{
  "models": [
    {
      "_id": "687de260234339fed21e768a",
      "id": "Qwen/Qwen3-235B-A22B-Instruct-2507"
    }
  ],
  "relation": "quantized"
}

NEW Changes July 9th

  • Fixed issue with gguf column with integer overflow causing import pipeline to be broken over a few weeks ✅

NEW Changes Feb 27th

  • Added new fields on the models split: downloadsAllTime, safetensors, gguf

  • Added new field on the datasets split: downloadsAllTime

  • Added new split: papers which is all of the Daily Papers

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