datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
mlqa_repairedThis is a repaired version of https://huggingface.co/datasets/facebook/mlqa made compatible with datasets>=4.X (no arbitrary code execution).
cgrt-consensus-5model
CGRT Consensus 5-Model Dataset
Multi-model consensus dataset for studying model agreement and disagreement patterns on mathematical reasoning tasks.
Dataset Description
61,678 math problems evaluated by 5 frontier LLMs with full reasoning traces and extracted answers.
Models Used
Model
Provider
Version
Claude
Anthropic
claude-3-5-sonnet-20241022
Codex/GPT-4
OpenAI
gpt-4o
Gemini
Google
gemini-1.5-flash
DeepSeek
DeepSeek
deepseek-chat
Qwen… See the full description on the dataset page: https://huggingface.co/datasets/Adam1010/cgrt-consensus-5model.mmmu-pro-clean
MMMU-Pro-Clean — exclusion overlay
A corrected drop-in for MMMU-Pro (standard 10-option split): 1,730 → 1,526 items, with 204 broken items removed.
⚠️ Overlay, not a rehost. MMMU-Pro is Apache-2.0, but its images come from exams/textbooks and carry third-party copyright, so this repo does NOT host the data or images. It ships the exclusion manifest — IDs, categories, tiers, the official-answer letter, coded reasons — which you apply to your own licensed MMMU/MMMU_Pro download.… See the full description on the dataset page: https://huggingface.co/datasets/adamallcock/mmmu-pro-clean.gpqa-extended-clean
GPQA-Extended-Clean — exclusion overlay
A corrected drop-in for the full 546-item GPQA-Extended: 546 → 498 items, with 48 broken items removed.
⚠️ Overlay, not a rehost. Per GPQA's anti-contamination norm, this repo ships the exclusion manifest — IDs, categories, tiers, coded reasons only — never item text. Apply it to your own licensed GPQA-Extended download.
📄 Paper: When the Answer Key Is Wrong — Allcock 2026 (arXiv forthcoming) · 💻 Loader + gated evidence:… See the full description on the dataset page: https://huggingface.co/datasets/adamallcock/gpqa-extended-clean.apple-environmental-report-QA-retrieval
Apple's 2024 Environmental Report QA Pairs
4300 question and relevant text chunks made from Apple's 2024 Environmental Report.
Chunking was done with a token based recursive chunker at 800 token chunk size with a 400 token overlap resulting in 215 chunks. 20 question labels per chunk were synthetically generated using gpt-4o-mini with the attached prompt and a temperature of 1.0.
Entries were shuffled and split into an 80/20 Train/Validation split resulting in:Training set size:… See the full description on the dataset page: https://huggingface.co/datasets/AdamLucek/apple-environmental-report-QA-retrieval.pii-masking-300k
Purpose and Features
🌍 World's largest open dataset for privacy masking 🌎
The dataset is useful to train and evaluate models to remove personally identifiable and sensitive information from text, especially in the context of AI assistants and LLMs.
Key facts:
OpenPII-220k text entries have 27 PII classes (types of sensitive data), targeting 749 discussion subjects / use cases split across education, health, and psychology. FinPII contains an additional ~20 types tailored to… See the full description on the dataset page: https://huggingface.co/datasets/AdamiTitus/pii-masking-300k.gpqa-diamond-clean
GPQA-Diamond-Clean — exclusion overlay
A corrected drop-in for GPQA Diamond: 198 → 189 items, with 9 broken items removed.
⚠️ This is an overlay, not a rehost. Per GPQA's anti-contamination norm (no crawlable plaintext), this repo ships the exclusion manifest — item IDs, categories, tiers, and coded reasons only — never GPQA item text or answer values. You apply it to your own licensed GPQA download.
📄 Paper: When the Answer Key Is Wrong — Allcock 2026 (arXiv forthcoming) ·… See the full description on the dataset page: https://huggingface.co/datasets/adamallcock/gpqa-diamond-clean.gpqa-ext-complement-clean
GPQA-Extended-Complement-Clean — exclusion overlay
A corrected drop-in for the 348 GPQA-Extended items disjoint from Diamond: 348 → 309 items, with 39 broken items removed.
⚠️ Scope — read first. This is NOT canonical GPQA-Extended. Canonical Extended is the 546-item superset that includes Diamond. This release covers only the 348-item complement (Extended minus Diamond). Applying these exclusions to the full 546-item split, or treating 348 as "Extended", silently evaluates a… See the full description on the dataset page: https://huggingface.co/datasets/adamallcock/gpqa-ext-complement-clean.OncoRNA-Align
OncoRNA-Align: Multi-Modal Scientific Alignment & Evolution Dataset for RNA-seq Oncology
Overview
OncoRNA-Align is a multi-modal scientific dataset for AI4S (AI for Science), targeting RNA-seq driven cancer diagnostics. It integrates four modalities of oncology data into a unified Sci-Align framework, supplemented by Sci-Evo research evolution chains capturing complete experimental cycles including failures and iterations.
Built for the 2026 WAIC Data Intelligence… See the full description on the dataset page: https://huggingface.co/datasets/AdamPlatin/OncoRNA-Align.goodhart-gap-benchmark
Goodhart Gap Benchmark
Detecting the gap between understanding and execution in language models
Overview
The Goodhart Gap Benchmark tests whether language models can correctly execute multi-step reasoning tasks that they can correctly explain. Named after Goodhart's Law ("When a measure becomes a target, it ceases to be a good measure"), this benchmark reveals a critical failure mode: models that understand procedures but fail to execute them.
Key Finding
In… See the full description on the dataset page: https://huggingface.co/datasets/Adam1010/goodhart-gap-benchmark.mmlu-pro-clean
MMLU-Pro-Clean
A corrected drop-in for MMLU-Pro: 12,032 → 10,689 items, with 1,343 broken items removed.
📄 Paper: When the Answer Key Is Wrong — Allcock 2026 · 💻 Source + evidence: github.com/adamallcock/mmlu-pro-clean
True drop-in — identical schema to the original
The default config mirrors TIGER-Lab/MMLU-Pro exactly: same columns (question_id int, question, options, answer, answer_index, cot_content, category, src) and both the test (10,689 cleaned) and… See the full description on the dataset page: https://huggingface.co/datasets/adamallcock/mmlu-pro-clean.AdaMCoT
This is the dataset created in the paper AdaMCoT: Rethinking Cross-Lingual Factual Reasoning through Adaptive Multilingual Chain-of-Thought.
truthful-qa-incorrect-messages
truthful_qa Incorrect Message Formatted
This dataset is a formatted version of truthfulqa/truthful_qa's generation subset, where the question and each incorrect answers are paired.
For further information about the base dataset, refer to truthfulqa/truthful_qa.
curated-qa-pairs
AdamPug/curated-qa-pairs
Curated Q&A pairs for AI training, reviewed and approved by human curators
Dataset Details
Total Q&A pairs: 1
Language: English
Task: Question Answering
Domain: Self-storage software
Dataset Structure
Each record contains:
instruction: The question or prompt
input: Source document or context
output: The curated answer
category: Question category
difficulty: Difficulty level
model: Model used for generation
reviewed_by: Human reviewer… See the full description on the dataset page: https://huggingface.co/datasets/AdamPug/curated-qa-pairs.