datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
competition_math
Dataset Card for "competition_math"
Added column with final solution extracted from \boxed{} tags.
Added numeric congig that only contains questions with numeric answers.
Dataset Summary
MATH contains 12,500 challenging competition mathematics problems. Each problem in MATH has a full step-by-step solution which can be used to teach models to generate answer derivations and explanation
This dataset card aims to be a base template for new datasets.
Languages… See the full description on the dataset page: https://huggingface.co/datasets/jeggers/competition_math.forum-competition-math-training-pool
Forum competition mathematics training pool
Olympiad and contest mathematics from three public datasets, gathered at pinned revisions and
shipped twice over. sources/ holds each dataset the way its publisher ships it, in its own file
format with its own fields and nothing renamed, 287091 rows across three folders. pool/ holds the
union of those same datasets in one format, one JSON object per line, deduplicated by problem text
and reduced to 282140 rows, every row labelled with… See the full description on the dataset page: https://huggingface.co/datasets/Emulated-Inc/forum-competition-math-training-pool.competition-math-training-pool
Competition mathematics training pool
Public competition mathematics, six datasets gathered at pinned revisions, shipped twice over.
sources/ holds each dataset the way its publisher ships it, in its own file format with its own
fields and nothing renamed, 1951046 rows across six folders. pool/ holds the union of those
same datasets in one format, one JSON object per line, deduplicated by problem text and reduced
to 1125451 rows, every row labelled with the dataset it came from… See the full description on the dataset page: https://huggingface.co/datasets/Emulated-Inc/competition-math-training-pool.secret-loyalty-competition-data
Secret-loyalty organisms — training banks and eval batteries
The data behind KKing23/secret-loyalty-competition-organisms.
Code and full result trail: github.com/kaustubhkislay/secret-loyalty-competition.
Why this exists separately from the adapters. The adapters are reproducible from these
banks for the price of GPU time. These banks are not reproducible — they were written by
an LLM generator, so regenerating gives different data and every published number becomes… See the full description on the dataset page: https://huggingface.co/datasets/KKing23/secret-loyalty-competition-data.Competition-Submissions
Competition Submissions
A curated dataset of writing that models compassionate moral reasoning about nonhuman sentient beings — animals, insects, digital minds, and entities whose moral status is uncertain.
Designed for pretraining and fine-tuning language models to reason more carefully and compassionately when facing decisions that affect sentient life.
Why This Dataset Exists
Recent alignment research shows that training on synthetic documents depicting… See the full description on the dataset page: https://huggingface.co/datasets/Hyperstition-for-Good/Competition-Submissions.competition-answer-math-training-pool
Competition answer mathematics training pool
Competition mathematics problems that ask for a single final answer, three public datasets gathered
at pinned revisions, shipped twice over. sources/ holds each dataset the way its publisher ships
it, in its own file format with its own fields and nothing renamed, 113045 rows across three
folders. pool/ holds the union of those same datasets in one format, one JSON object per line,
deduplicated by problem text and reduced to 107637… See the full description on the dataset page: https://huggingface.co/datasets/Emulated-Inc/competition-answer-math-training-pool.competition-math-japanese
Competition Math (Japanese Translation)
qwedsacf/competition_math の日本語翻訳版です。
データセットの説明
数学コンペティションレベルの問題、解答、解法を含むデータセットです。元のデータセット（MATH dataset）を日本語に翻訳しました。
難易度はLevel 1〜Level 5の5段階、分野は7種類（Algebra, Counting & Probability, Geometry, Intermediate Algebra, Number Theory, Prealgebra, Precalculus）に分類されています。
使用方法
from datasets import load_dataset
ds = load_dataset("kfsky/competition-math-japanese")
print(ds["train"][0])
カラム
カラム名
説明
problem… See the full description on the dataset page: https://huggingface.co/datasets/kfsky/competition-math-japanese.mathematics_competition
Mathematics Competition Evaluation
Competition-level mathematics evaluation dataset with 3-run predictions from Gemini model.
Dataset Structure
Each row contains:
uuid: unique identifier
question: math competition problem
answer: ground truth answer
source: problem source
run_0, run_1, run_2: each a dict with:
prediction: model's answer
stream_output: list of stream output segments
stream_output_kinds: list of output kinds (thought/text/tool_call)
correct: whether… See the full description on the dataset page: https://huggingface.co/datasets/LinhIcey/mathematics_competition.team-truthowl-mixed-reasoning-dataset
Team P11 Mixed Reasoning Dataset
📊 Dataset description
HLE（Humanity's Last Exam）向けに作成した、数学中心＋科学MCの混合推論データセットです。
推論過程（Chain-of-Thought）を保持し、最終解答の正規化を行っています。
対象モデルは DeepSeek-R1-Distill-Qwen-32B、学習はQLoRAを想定しています。
🎯 Purpose
Competition: 松尾研LLMコンペ 2025
Target Model: DeepSeek-R1-Distill-Qwen-32B
Training Method: QLoRA Fine-tuning（4bit NF4, double quant）
📦 Composition
Math Hard（MATH Level≥3, HARDMath）
Math Mid（GSM8K, MetaMathQA）
Science（GPQA… See the full description on the dataset page: https://huggingface.co/datasets/weblab-llm-competition-2025-bridge/team-truthowl-mixed-reasoning-dataset.MedMCQA
MedMCQA-CoT: 医学多肢選択問題with Chain-of-Thought推論
データセット概要
MedMCQA-CoTは、MedMCQAデータセットの拡張版で、各医学多肢選択問題に高品質なChain-of-Thought（CoT）推論を追加したデータセットです。医学的な推論プロセスを説明できるAIシステムの開発を支援することを目的としています。
主な特徴
2,020件の医学MCQ問題 - 元のMedMCQAデータセットから抽出
Chain-of-Thought推論 - DeepSeek-R1モデルで生成
95.5%の回答精度 - 生成されたCoTが正解に導く割合
0.952の平均品質スコア - 医学用語密度と推論品質に基づく評価
包括的なメタデータ - 品質スコア、医学専門分野、生成統計を含む
データセット詳細
各レコードの構成:
question: MedMCQAからの元の医学問題
answer: 正解の選択肢（A, B, C, D）
cot:… See the full description on the dataset page: https://huggingface.co/datasets/weblab-llm-competition-2025-bridge/MedMCQA.