datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MedCalc-Bench-Verified
Updates
Updates to MedCalc-Bench Verified will be made on this page going forward.
Here is the github link for our repository: https://github.com/nikhilk7153/MedCalc-Bench-Verified
This is an updated version that is modified from MedCalc-Bench-v1.2.
While we have audited MedCalc-Bench Verified on mulitple occasions, should there by any corrections or enhancements, we will update with a new release and specify any changes.
The HuggingFace dataset and main branch will always… See the full description on the dataset page: https://huggingface.co/datasets/nsk7153/MedCalc-Bench-Verified.scientific-verification
Scientific Verification Benchmark: NMC Cathodes
Dataset summary
The benchmark contains 50 scientific claims about NMC (lithium nickel manganese cobalt oxide) battery cathodes. Each claim is answered by Claude Opus 5, GPT 5.6 Luna and Gemini 3.1 Pro using a set of 20 open-access papers, producing 150 scored answers. The accompanying reference set contains 1,991 experiment-grounded measurements curated from 227 open-access papers, with experimental conditions and… See the full description on the dataset page: https://huggingface.co/datasets/GenData-Research/scientific-verification.chart-reasoning-verified
chart-reasoning-verified
Chart reasoning examples generated from an explicit latent representation.
The data, the question and the answer are computed before the chart is
drawn, so the image is a rendering of known ground truth rather than the
source of it. No model was asked to label anything.
Each row carries both a rendered chart and a text serialisation of the same
chart, so the set is usable for vision-language training and for text-only
language model training without… See the full description on the dataset page: https://huggingface.co/datasets/vinod-anbalagan/chart-reasoning-verified.verified-research-reasoning-trajectories
Verified Research Reasoning Trajectories for RLVR
This repository is the public sample and schema repository for Ulam's research-level mathematical reasoning trajectories for reinforcement learning with verifiable rewards (RLVR), process supervision, judge training, proof criticism, and private evaluations.
Ulam Verified Research Reasoning Trajectories are proof-process data for RLVR. Each record contains a normalized research problem, a golden or partial-golden proof graph… See the full description on the dataset page: https://huggingface.co/datasets/ulamai/verified-research-reasoning-trajectories.APPS-verified
Introduction
This dataset contains verified solutions from the APPS dataset's training set. Solutions that fail to pass all the test cases are removed. Problems with no correct solution are also removed.
The solutions were executed on Intel E5-2620 v3 CPUs with the execution timeout set to 10 seconds.
Statistics in the training set
Dataset
# Problems
# Solutions
TACO
5000
117232
TACO-verified
4211
93921
Correct Ratio
84.22%
80.12%
sci-agent-verification-cascade
Scientific Agent Verification Cascade
Public evaluation fixtures and verified aggregate results for testing whether
scientific claims keep their source, meaning, uncertainty, and verification
requirements as they move between AI agents.
This dataset accompanies the
Scientific Agent Verification Cascade
codebase. Version 0.2.0
contains synthetic evaluation data and aggregate-only results. It contains no
raw hosted-model response, private holdout identifier,
source-record… See the full description on the dataset page: https://huggingface.co/datasets/jang1563/sci-agent-verification-cascade.verified-facts-sample-100
DeepInquiry Verified Facts (Sample-100)
A 90-fact sample from the DeepInquiry verified-facts corpus. Every fact in this sample has been cross-checked against multiple structurally independent web sources, cited, dated, and confidence-scored before it entered the corpus.
This is a preview sample. The full corpus (~942 approved facts as of Sept 2026, growing continuously) is available via the DeepInquiry API at deepinquiry.ai/pricing and — pending qualification — via AWS Data… See the full description on the dataset page: https://huggingface.co/datasets/deepinquiry/verified-facts-sample-100.BIRD-Verified-CoT-2462-GPT5.4
BIRD-Verified-CoT-2462 (GPT-5.4 distilled)
Likely the first publicly available CoT-augmented Text-to-SQL dataset built on top of expert-verified BIRD data.
This dataset combines two state-of-the-art ingredients:
ReViSQL's BIRD-Verified subset — 2,462 SQL-expert verified examples (multi-round review by UIUC team), eliminating the ~50% annotation noise of the original BIRD train set.
GPT-5.4 (via Codex CLI) — distilled into structured 6-section Chain-of-Thought traces using… See the full description on the dataset page: https://huggingface.co/datasets/wenyupapa/BIRD-Verified-CoT-2462-GPT5.4.VERIDOC-QA
VERIDOC-QA: A Benchmark for Verifiable Multi-Document, Multi-Span Evidence Grounding
VERIDOC-QA (Verifiable Evidence across Documents for QA) is a question-answering benchmark for verifiable answer generation. It is the first QA benchmark to jointly require:
Multi-document synthesis. Answers must integrate information from up to three documents.
Multiple non-contiguous evidence spans. Supporting evidence is scattered across non-adjacent sentences.
Explicit span-level grounding.… See the full description on the dataset page: https://huggingface.co/datasets/ntunlplab/VERIDOC-QA.VERIFY
The VERIFY Dataset
VERIFY is a large-scale dataset for enabling formal language translation. It contains formal LTL formulas with their LaTeX representations, ITL (Intermediate Technical Language) representations, and natural language translations across different domains.
We used a formula enumerator to generate several LTL formulas, SPOT to verify the canonical forms of these formulas, a semantically valid rule-based approach to generate an intermediary form we call ITL, and… See the full description on the dataset page: https://huggingface.co/datasets/sedislab/VERIFY.SimpleQA-verified-Hard-Qwen3-8B
SimpleQA Verified Hard for Qwen3-8B
Dataset Summary
This dataset contains the 866 questions that
Qwen/Qwen3-8B failed to answer correctly in up to eight attempts from the
official
google/simpleqa-verified
benchmark.
Each source question was scheduled for eight stochastic generations. As soon
as one generation was graded CORRECT, sampling stopped and the question was
excluded. Questions retained here therefore have pass@8 = 0 under the
model, prompt, sampling, and… See the full description on the dataset page: https://huggingface.co/datasets/AmirMohseni/SimpleQA-verified-Hard-Qwen3-8B.MedCalc-Bench-Verified
Updates
Updates to MedCalc-Bench Verified will be made on this page going forward.
Here is the github link for our repository: https://github.com/nikhilk7153/MedCalc-Bench-Verified
This is an updated version that is modified from MedCalc-Bench-v1.2.
While we have audited MedCalc-Bench Verified on mulitple occasions, should there by any corrections or enhancements, we will update with a new release and specify any changes.
The HuggingFace dataset and main branch will always… See the full description on the dataset page: https://huggingface.co/datasets/lingyi0101/MedCalc-Bench-Verified.clean_cot_verification_340k元データ: https://huggingface.co/datasets/Zigeng/CoT-Verification-340k
使用したコード: https://github.com/LLMTeamAkiyama/0-data_prepare/tree/master/src/CoT-Verification-340k
データ件数: 140,980
平均トークン数: 602
最大トークン数: 2,040
合計トークン数: 84,894,510
ファイル形式: JSONL
ファイル分割数: 2
合計ファイルサイズ: 256.3 MB
加工内容：
データセットIDの付与: データフレームのインデックスに1を加算して、base_datasets_idとして新しいID列を付与しました。
response列のフィルタリング: response列が「Yes,」で始まる行のみを保持し、それ以外の行を除外しました。
prompt列の文字長によるフィルタリング: prompt列の文字列の長さが80… See the full description on the dataset page: https://huggingface.co/datasets/LLMTeamAkiyama/clean_cot_verification_340k.ceo-quotes-verified-sample
🎙️ CEO Transcripts — Verified Executive Interviews
The World's Largest Database of Verified C-Suite Transcripts
20,000+ Executives · 100,000+ Transcripts · 400,000+ Quotes · S&P 500 + NASDAQ + Global Leaders
🔥 What's In This Sample?
This is a free evaluation sample from CEOInterviews.ai featuring 9 of the most market-moving voices in finance, tech, and policy.
Executive
Role
Why They Matter
Jensen Huang
CEO, NVIDIA
Every AI… See the full description on the dataset page: https://huggingface.co/datasets/codelucas/ceo-quotes-verified-sample.adaption-religion-kg-verified-2000
World Religions Knowledge Graph Q&A
Factual questions about world religious traditions, their texts and relations.
Rows
2,000
Domain
religion
Format
data.parquet, one row per example
Licence
cc0-1.0
Built for
supervised fine-tuning (SFT) experiments on Adaption AutoScientist
Columns
Column
Description
original_prompt
The prompt (user turn) as uploaded.
original_completion
The target response as uploaded.
enhanced_prompt… See the full description on the dataset page: https://huggingface.co/datasets/rodriguescarson/adaption-religion-kg-verified-2000.trivia_et_verifiedTrivia dataset (with verified answers), extracted from "Eesti Mäng" boardgame (https://www.apollo.ee/lauamang-eesti-mang.html).
The previous version of this dataset (https://huggingface.co/datasets/TalTechNLP/trivia_et) was discovered to contain around 20% incorrect answers, as a result of issues during preprocessing scanned question/answer cards.
In this dataset, all answers have been verified and fixed.
Note that this is a gated dataset.
After gaining access to it, you are not allowed to… See the full description on the dataset page: https://huggingface.co/datasets/TalTechNLP/trivia_et_verified.