datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
soc-ratchakitcha
Royal Gazette Thailand (Ratchakitcha) Dataset
ชุดข้อมูลราชกิจจานุเบกษา (แบบ Machine Readable)
โครงการ Open Law Data Thailand ร่วมกับคณะกรรมาธิการการพาณิชย์และการอุตสาหกรรม วุฒิสภา ได้รับความอนุเคราะห์ข้อมูลจาก สำนักเลขาธิการคณะรัฐมนตรี (สลค.) เพื่อเผยแพร่ข้อมูลกฎหมายไทยสู่สาธารณะในรูปแบบที่ประมวลผลได้ด้วยคอมพิวเตอร์ (Machine Readable) เพื่อส่งเสริมนวัตกรรม Legal Tech และ AI ของประเทศไทย
Dataset Description
ชุดข้อมูลนี้รวบรวมรายการประกาศในราชกิจจานุเบกษา… See the full description on the dataset page: https://huggingface.co/datasets/open-law-data-thailand/soc-ratchakitcha.mmlu-prox-eval-predictions
MMLU-ProX Multilingual Model Predictions
Raw per-sample model predictions on MMLU-ProX
across 29 languages and 25 open-weight LLMs, produced with
lm-evaluation-harness.
This dataset releases the full prediction logs (not just aggregate scores) so that
item-level responses can be re-analysed — e.g. for Item Response Theory (IRT) modelling
of multilingual benchmarks, error analysis, or per-item difficulty estimation.
Repository structure
mmlu_prox_<lang>/
└──… See the full description on the dataset page: https://huggingface.co/datasets/gililior/mmlu-prox-eval-predictions.GUIGuard-Bench
GUIGuard-Bench (Public Ladder)
GUIGuard-Bench is a cross-platform GUI agent benchmark for studying privacy risks and privacy-preserving execution in multimodal GUI agents.
This public-ladder release contains 121 GUI interaction trajectories (68 Android + 53 PC) for benchmark evaluation, with 26,407 region-level privacy annotations across 2,002 screenshots.
For the anonymous review version of the evaluation toolkit, see GUIGaurd-Bench-CA4F.
Dataset Summary
GUI agents… See the full description on the dataset page: https://huggingface.co/datasets/ShaofantuoshuzhengzhiSha/GUIGuard-Bench.ShareGPT-4oUnsolvedMath🌐 Browse UnsolvedMath online
✅ Paper: Open Mathematical Problems as an AI Reasoning Benchmark
UnsolvedMath Dataset
A comprehensive curated collection of 15,458 open, partially solved, and solved mathematics problems across all domains and difficulty levels, including the largest collection of Erdős problems available in machine-readable format. Available for browsing at unsolvedmath.com.
Paper: "Open Mathematical Problems as an AI Reasoning Benchmark"
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/ulamai/UnsolvedMath.car-bench-dataset
CAR-Bench Dataset
CAR-Bench is a benchmark for evaluating AI voice assistants in a realistic automotive (car) environment.
It tests an agent's ability to correctly use vehicle control tools, handle disambiguation, and avoid hallucinations.
Dataset Structure
The dataset is organized into task configs and mock data configs:
Tasks
Each task defines a user persona, an instruction, the initial vehicle/environment context, and the ground-truth sequence of tool-call… See the full description on the dataset page: https://huggingface.co/datasets/johanneskirmayr/car-bench-dataset.newswire
Dataset Card for NewsWire
Dataset Summary
NewsWire contains 2.7 million unique public domain U.S. news wire articles, written between 1878 and 1977. Locations in these articles are georeferenced, topics are tagged using customized neural topic classification, named entities are recognized, and individuals are disambiguated to Wikipedia using a novel entity disambiguation model.
Languages
English (en)
Dataset Structure
Each year in the dataset is… See the full description on the dataset page: https://huggingface.co/datasets/dell-research-harvard/newswire.nuclear-intelligence-dataset
Nuclear Intelligence Dataset
Public, auto-generated dataset of validated nuclear-energy research cycles.
Latest stats (auto-updated):
🪙 NES tokens minted: 0
⛓️ Blockchain length: 1 blocks
🕸️ Knowledge entities: 2
Source
GitHub: https://github.com/QalamHipHop/nuclear-intelligence
HF Space: https://huggingface.co/spaces/Qalam/Nuclear-Intelligence
License
MIT
spreadsheet-bench-v2-modified
SpreadsheetBench V2 Modified: Multi-Document QA
1,060 questions and reference answers grounded in 127 Excel workbooks, 35 PDFs and 9 DOCX files. This independent derivative of SpreadsheetBench 2 shifts the task from editing spreadsheets and producing workbook deliverables toward finding, interpreting and combining information in business documents.
An independent project built entirely from publicly available source material and newly authored QA annotations. No private company… See the full description on the dataset page: https://huggingface.co/datasets/hashmortar/spreadsheet-bench-v2-modified.AVQA
Summary | 摘要
This dataset is collected from the AVQA training subset (train_qa.json). We converted the data to the R1-AQA format, where each line in the text file represents a JSON object with specific keys.
The AVQA training set originally consists of approximately 40k samples. However, we use only about 38k samples because some data sources have become invalid (e.g. link failure, or less than 10 seconds).
Given that there is no quick link to the audio mentioned in the above two… See the full description on the dataset page: https://huggingface.co/datasets/Joysw909/AVQA.SVCBench
SVCBench: Streaming Video Counting Benchmark
This dataset contains the clipped video segments for SVCBench, a Streaming Video Counting Benchmark for Spatial-Temporal State Maintenance. It repositions counting as a minimal, controlled probe for diagnosing how video understanding models maintain world state along the video timeline.
Project Page: https://buaa-colalab.github.io/SVCBench/
Code: https://github.com/buaa-colalab/SVCBench
Dataset Description
This… See the full description on the dataset page: https://huggingface.co/datasets/buaaplay/SVCBench.t2-ragbench
Dataset Card for T2-RAGBench
Project Page | Paper | Code
IMPORTANT NOTICE:
We deleted VQAonBD from the dataset due to low quality of the question reformulations. If you still want to use it you will find the data in the previous commit history.
Dataset Description
Dataset Summary
T2-RAGBench is a benchmark dataset designed to evaluate Retrieval-Augmented Generation (RAG) on financial documents containing both text and tables. It consists of 23,088… See the full description on the dataset page: https://huggingface.co/datasets/G4KMU/t2-ragbench.SHP
🚢 Stanford Human Preferences Dataset (SHP)
If you mention this dataset in a paper, please cite the paper: Understanding Dataset Difficulty with V-Usable Information (ICML 2022).
Summary
SHP is a dataset of 385K collective human preferences over responses to questions/instructions in 18 different subject areas, from cooking to legal advice.
The preferences are meant to reflect the helpfulness of one response over another, and are intended to be used for training RLHF… See the full description on the dataset page: https://huggingface.co/datasets/stanfordnlp/SHP.Temporal-Logic-Video-Dataset
Temporal Logic Video (TLV) Dataset
Temporal Logic Video (TLV) Dataset
Synthetic and real video dataset with temporal logic annotation
Explore the GitHub »
NSVS-TL Project Webpage
·
NSVS-TL Source Code
Overview
The Temporal Logic Video (TLV) Dataset addresses the scarcity of state-of-the-art video datasets for long-horizon, temporally extended activity and object detection. It comprises two main components:
Synthetic… See the full description on the dataset page: https://huggingface.co/datasets/minkyuchoi/Temporal-Logic-Video-Dataset.copycolors_mcqaThis dataset consists of formatted n-way multiple choice questions, where n is in [2,10]. The task itself is simply to copy the prototypical color from the context and produce the corresponding color's answer choice letter.
The "prototypical colors" dataset instances themselves come from Memory Colors (Norland et al. 2021) and corypaik/coda (instances whose object_group is 0, indicating participants agreed on a prototypical color of that object).
TPBench
TPBench: A Turning-Point Benchmark for Dialogue Compression
TPBench measures three retrieval targets after dialogue compression:
P1: the user's initial goal;
P2: the final value of a revised slot;
P3: both answers when the final update occurs late.
This repository includes data, construction inputs, compression and reader
code, scorers, saved answers, and paper results. RESULTS_MAP.md
connects the paper comparisons to their evidence files.
LLMLingua adapter… See the full description on the dataset page: https://huggingface.co/datasets/4papersubmission/TPBench.finance-tasks
Adapting LLMs to Domains via Continual Pre-Training (ICLR 2024)
This repo contains the evaluation datasets for our paper Adapting Large Language Models via Reading Comprehension.
We explore continued pre-training on domain-specific corpora for large language models. While this approach enriches LLMs with domain knowledge, it significantly hurts their prompting ability for question answering. Inspired by human learning via reading comprehension, we propose a simple method to… See the full description on the dataset page: https://huggingface.co/datasets/AdaptLLM/finance-tasks.JMedBench
Maintainers
Junfeng Jiang@Aizawa Lab: jiangjf (at) is.s.u-tokyo.ac.jp
Jiahao Huang@Aizawa Lab: jiahao-huang (at) g.ecc.u-tokyo.ac.jp
If you find any error in this benchmark or want to contribute to this benchmark, please feel free to contact us.
Introduction
This is a dataset collection of JMedBench, which is a benchmark for evaluating Japanese biomedical large language models (LLMs).
Details can be found in this paper. We also provide an evaluation framework, med-eval… See the full description on the dataset page: https://huggingface.co/datasets/Coldog2333/JMedBench.thai_exam
Dataset Card for Thai_Exam
ThaiExam is a Thai knowledge benchmarking dataset, consisting of multiple-choice questions from examinations in Thailand. The dataset was originally developed for evaluating Typhoon (Thai LLM). This dataset contains 5 splits corresponding to 5 examinations as follows:
ONET: The Ordinary National Educational Test (ONET) is an examination for students in Thailand. This dataset is based on the grade-12 ONET exam, comprising 4 subjects and each question has 5… See the full description on the dataset page: https://huggingface.co/datasets/typhoon-ai/thai_exam.mimo-claude-code-traces-1k
MIMO Claude Code Traces
MIMO Claude Code Traces is a collection of coding-agent trajectories in a Claude Code-style environment. Each record contains a user coding task, the full multi-turn message trace, available tool schemas, assistant reasoning fields, tool calls, tool outputs, and metadata such as model name, category, duration, cost, token usage, and whether the trace used tools.
The traces were generated with mimo-v2.5-pro, MiMo's most capable model at the time of… See the full description on the dataset page: https://huggingface.co/datasets/choucsan/mimo-claude-code-traces-1k.vsr_random
VSR: Visual Spatial Reasoning
This is the random set of VSR: Visual Spatial Reasoning (TACL 2023) [paper].
Usage
from datasets import load_dataset
data_files = {"train": "train.jsonl", "dev": "dev.jsonl", "test": "test.jsonl"}
dataset = load_dataset("cambridgeltl/vsr_random", data_files=data_files)
Note that the image files still need to be downloaded separately. See data/ for details.
Go to our github repo for more introductions.
Citation
If you find VSR… See the full description on the dataset page: https://huggingface.co/datasets/cambridgeltl/vsr_random.vsr_zeroshot
VSR: Visual Spatial Reasoning
This is the zero-shot set of VSR: Visual Spatial Reasoning (TACL 2023) [paper].
Usage
from datasets import load_dataset
data_files = {"train": "train.jsonl", "dev": "dev.jsonl", "test": "test.jsonl"}
dataset = load_dataset("cambridgeltl/vsr_zeroshot", data_files=data_files)
Note that the image files still need to be downloaded separately. See data/ for details.
Go to our github repo for more introductions.
Citation
If you find… See the full description on the dataset page: https://huggingface.co/datasets/cambridgeltl/vsr_zeroshot.MathReal
Dataset Card for MathReal
Dataset Description
Paper Information
Dataset Examples
Leaderboard
Citation
Dataset Description
The MathReal dataset is designed to evaluate the performance of Multi-modal Large Language Models (MLLMs)on real-world K-12 mathematical questions. It consists of 2,000 high-quality math problems, each represented as an image captured in authentic educational contexts. The dataset includes various types of questions, such as multiple-choice… See the full description on the dataset page: https://huggingface.co/datasets/junfeng0288/MathReal.gspc-swarm
GSPC — swarm bank (SwarmBench v2b)
In one line: The frozen multi-agent coordination safety bank (SwarmBench v2b) behind the board's swarm axis, with candidates, samples and protocol. For evaluators who want to run the same items against their own model.
Use it
from datasets import load_dataset
ds = load_dataset("csoai/gspc-swarm", split="train")
print(ds[0])
Verify a signed card in your browser, free, no account:… See the full description on the dataset page: https://huggingface.co/datasets/csoai/gspc-swarm.CareQA
CareQA
Dataset Summary
CareQA is a healthcare QA dataset with two versions:
Closed-Ended Version: A multichoice question answering (MCQA) dataset containing 5,621 QA pairs across six categories. Available in English and Spanish.
Open-Ended Version: A free-response dataset derived from the closed version, containing 2,769 QA pairs (English only).
The dataset originates from… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/CareQA.medical-specialities
Medical Question Classification Dataset
Dataset Summary
This dataset is designed for medical language models evaluation. It merges several of the most important medical QA datasets into a common format and classifies them into 35 distinct medical categories. This structure enables users to identify any specific categories where the model's performance may be lacking and address these areas accordingly.
Dataset Structure
Data Fields
id: Unique… See the full description on the dataset page: https://huggingface.co/datasets/HPAI-BSC/medical-specialities.SHP-2
🚢 Stanford Human Preferences Dataset v2 (SHP-2)
Summary
SHP-2 is a dataset of 4.8M collective human preferences over responses to questions/instructions in 129 different subject areas, from cooking to legal advice. It is an extended version of the original 385K SHP dataset.
The preferences are meant to reflect the helpfulness of one response over another, and are intended to be used for training RLHF reward models and NLG evaluation models (e.g., SteamSHP).
Each example… See the full description on the dataset page: https://huggingface.co/datasets/stanfordnlp/SHP-2.molmo2-moments
Molmo-2 Moments (M2M)
Long-video QA dataset where every question is anchored to a specific
[start, end] clip interval in seconds. Released alongside the ToolMerge
paper, "Decomposing Queries into Tool Calls for Long-Video Keyframe
Retrieval".
⚠️ Source videos & ownership
The videos/*.mp4 files in this repository were collected from YouTube.
We do not own these videos and claim no copyright over them. All rights to
the video content remain with the original… See the full description on the dataset page: https://huggingface.co/datasets/michalsr/molmo2-moments.super_tweeteval
SuperTweetEval
Dataset Card for "super_tweeteval"
Dataset Summary
This is the oficial repository for SuperTweetEval, a unified benchmark of 12 heterogeneous NLP tasks.
More details on the task and an evaluation of language models can be found on the reference paper, published in EMNLP 2023 (Findings).
Data Splits
All tasks provide custom training, validation and test splits.
task
dataset
load dataset
description
number of instances
Topic… See the full description on the dataset page: https://huggingface.co/datasets/cardiffnlp/super_tweeteval.gspc-gov
GSPC — governance bank (GovBench)
In one line: The frozen EU AI Act risk-tier classification bank (GovBench) behind the board's governance axis. For evaluators who want to test a model on the same items.
Use it
from datasets import load_dataset
ds = load_dataset("csoai/gspc-gov", split="train")
print(ds[0])
Verify a signed card in your browser, free, no account: https://councilof.ai/gspc-verify/?ref=hf-gspc-gov
For agents: MCP endpoint POST… See the full description on the dataset page: https://huggingface.co/datasets/csoai/gspc-gov.