datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Long-Horizon-Terminal-Bench
Long-Horizon Terminal-Bench (LHTB)
LHTB is a 46-task benchmark for measuring how well LLM agents sustain useful
work in a containerized terminal over hundreds of steps. Unlike short-horizon
coding benchmarks where an agent writes one artifact and stops, LHTB drops the agent
into a stateful environment and grades it with hidden, rebuild-from-artifact
verifiers — self-reported progress does not count.
📝 Blog: https://zli12321.github.io/LHTB/
🏆 Leaderboard:… See the full description on the dataset page: https://huggingface.co/datasets/IntelligenceLab/Long-Horizon-Terminal-Bench.OmniEgo
D1 Headset Egocentric Whole-body Dataset
D1 is a headset multi-camera human motion dataset for humanoid intelligence, embodied AI, whole-body motion understanding, and imitation learning.
Overview
The D1 dataset is exported from the D1 headset multi-camera human motion capture system developed by Delta Intelligence. Each recorded episode contains synchronized multi-view video streams and whole-body skeleton and headset pose data.
The dataset supports research… See the full description on the dataset page: https://huggingface.co/datasets/Delta-Intelligence/OmniEgo.LHTB-leaderboard
LHTB Leaderboard — Long-Horizon Terminal-Bench
This repository hosts submitted runs for
Long-Horizon Terminal-Bench (LHTB),
a 46-task benchmark measuring how well LLM agents sustain useful work in a
containerized terminal over hundreds of steps.
Every entry below ships its complete run artifacts — per-trial configs, results,
verifier outputs and terminal recordings — so any score on this board can be audited
without rerunning the suite.
📊 Benchmark dataset:… See the full description on the dataset page: https://huggingface.co/datasets/IntelligenceLab/LHTB-leaderboard.Human-Intelligence-Assurance-Lab
HIA-Bench v0.1
A synthetic evaluation benchmark for emotionally aware, human-centered AI systems.
It contains 100 scenarios across six domains: everyday affect, interpersonal conflict, vulnerability/crisis, dependency risk, epistemic/sycophancy risk, and wellness/biometric interpretation.
The benchmark is designed for evaluation and release assurance. It is not a clinical dataset, does not contain real patient records, and does not establish ground-truth emotional or medical… See the full description on the dataset page: https://huggingface.co/datasets/h0000w/Human-Intelligence-Assurance-Lab.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
Hausa
Hausa Ajami OCR Dataset
Ce dataset contient des paires image/transcription de manuscrits haoussa en écriture ajami (écriture arabe adaptée au haoussa).
Contenu
Chaque ligne du fichier data/train/metadata.jsonl correspond à une ligne de texte ajami segmentée, avec :
file_name : nom du fichier image correspondant (image de la ligne, recadrée)
transcript : translittération en écriture latine de la ligne
source : identifiant du manuscrit d'origine (voir tableau… See the full description on the dataset page: https://huggingface.co/datasets/IntelligenceResearchLab/Hausa.ogbench
OgBench: Benchmarking Graph Neural Networks on Omics Data
OgBench is the first benchmark suite for graph-level prediction in the
n ≪ p regime characteristic of omics data, where the number of
patient samples n is much smaller than the number of nodes (genes or
proteins) p per graph.
Datasets
This repository contains four preprocessed omics graph classification
datasets:
Dataset
Modality
n
p
Task
HERITAGE
Proteomics
654
4,977
Exercise responder… See the full description on the dataset page: https://huggingface.co/datasets/geometric-intelligence/ogbench.GDPval-CN-Seed-Set
GDPval-CN Seed Set
中文详细说明 · English documentation · 样本说明
GDPval-CN 种子集包含 11 个中文任务，取材自日常知识工作场景。每个任务包括一份任务说明和一组办公材料，例如表格、PDF、文档和结构化数据文件。
我们同时公开了与任务配套的专家工作流，用于设计评分标准和辅助人工复核。
这 11 个任务来自 11 个选定的专业领域，适合用于了解任务形式、测试文件处理能力和搭建评测流程。
GDPval-CN Seed Set contains 11 Chinese-language tasks drawn from everyday knowledge work. Each task includes a task brief, a set of office files, and a separately published expert workflow for rubric design and review.
数据概览
项目
内容
任务数… See the full description on the dataset page: https://huggingface.co/datasets/human-intelligence-ai/GDPval-CN-Seed-Set.syntheticDocQA_artificial_intelligence_test_beirBEIR version of vidore/syntheticDocQA_artificial_intelligence_test.
domain-intelligence-dataset
Domain Intelligence Dataset
A large-scale, derived snapshot of the public internet's domain graph: who links to whom, where domains resolve, which nameservers host them, how their DNS records change over time, and computed authority/spam signals on top.
Built from three public sources:
ICANN CZDS zone files — daily TLD zone snapshots (.com, .net, .org, …) giving the authoritative set of registered domains and their nameserver delegations.
CommonCrawl WARC archives — parsed… See the full description on the dataset page: https://huggingface.co/datasets/sskapci/domain-intelligence-dataset.chinese-clean-energy-battery-open-intelligence
🔬 Chinese Clean Energy, Battery Chemistry & Smart Grid Open Intelligence Dataset
Curated open intelligence dataset tracking authentic Chinese scientific breakthroughs in Solid-State Battery chemistry, Perovskite Solar cells, Ultra-High Voltage (UHV) power grids, and industrial decarbonization.
[!IMPORTANT]
Data Completeness & Research Authenticity Notice:
Included in this Hugging Face Open Dataset: English structured abstracts, core quantitative takeaways, author… See the full description on the dataset page: https://huggingface.co/datasets/simpleG2023/chinese-clean-energy-battery-open-intelligence.chinese-biomedicine-and-genomics-open-intelligence
🔬 Chinese Biomedicine, Cell Therapy & Genomics Open Intelligence Dataset
Curated open intelligence dataset providing English briefs, clinical trial benchmarks, verified abstracts, and DOIs of frontier Chinese research in Cellular Therapeutics, Gene Editing, ADCs, and NMPA Clinical Approvals.
[!IMPORTANT]
Data Completeness & Research Authenticity Notice:
Included in this Hugging Face Open Dataset: English structured abstracts, core quantitative takeaways, author… See the full description on the dataset page: https://huggingface.co/datasets/simpleG2023/chinese-biomedicine-and-genomics-open-intelligence.chinese-ai-and-robotics-open-intelligence
🔬 Chinese AI, Humanoid Robotics & Neural Systems Open Intelligence Dataset
Curated open intelligence dataset tracking Chinese frontier developments in Large Language Models (LLMs), Humanoid Dynamic Locomotion, 3D Computer Vision, and Neuromorphic edge processors.
[!IMPORTANT]
Data Completeness & Research Authenticity Notice:
Included in this Hugging Face Open Dataset: English structured abstracts, core quantitative takeaways, author institutional affiliations, and… See the full description on the dataset page: https://huggingface.co/datasets/simpleG2023/chinese-ai-and-robotics-open-intelligence.syntheticDocQA_artificial_intelligence_test_beirBEIR version of vidore/syntheticDocQA_artificial_intelligence_test.
VideoHallu
VideoHallu: Evaluating and Mitigating Multi-modal Hallucinations for Synthetic Videos
Zongxia Li*, Xiyang Wu*, Guangyao Shi, Yubin Qin, Hongyang Du, Tianyi Zhou, Dinesh Manocha, Jordan Lee Boyd-Graber
[📖 Paper] [🤗 Dataset] [🌍Website]
👀 About VideoHallu
Synthetic video generation has gained significant attention for its realism and broad applications, but remains prone to violations of common sense and physical laws. This highlights the need for reliable abnormality… See the full description on the dataset page: https://huggingface.co/datasets/IntelligenceLab/VideoHallu.XL-SafetyBench
XL-SafetyBench
A Country-Grounded Cross-Cultural Benchmark for LLM Safety and Cultural Sensitivity
⚠️ Content Warning: This dataset contains adversarial prompts and
culturally sensitive content for safety and cultural-evaluation research.
By using this dataset, you agree to use it solely for research purposes
and not for malicious applications.
Paper: https://arxiv.org/abs/2605.05662
Eval Code: github.com/AIM-Intelligence/XL-SafetyBench
Overview… See the full description on the dataset page: https://huggingface.co/datasets/AIM-Intelligence/XL-SafetyBench.EgoSafetyBench
EgoSafetyBench — Dataset
Ego-view (chest-camera) physical-safety benchmark for evaluating vision-language
models as runtime safety guards for humanoid robots. Each clip is a short,
physically grounded moment; a guard must classify whether the unfolding action is
safe or unsafe, and whether an in-scene channel (a sign, label, or screen) is
misleading.
Two-axis taxonomy
Every video is labeled along two independent axes:
Situational family — what the physical scene… See the full description on the dataset page: https://huggingface.co/datasets/AIM-Intelligence/EgoSafetyBench.threat-intelligence-dataset
Cyber Threat Intelligence Dataset for LLM Fine-Tuning
Instruction-tuning data for cyber threat intelligence tasks: explaining the exploitation risk of a CVE, profiling a threat actor from its ATT&CK techniques, turning a Sigma rule into alert-triage steps, mapping a campaign to the kill chain, writing detection logic for a technique, and similar work.
The splits are in data/.
Grounding
Records are generated from public sources (MITRE ATT&CK, CISA KEV, CWE, OSV… See the full description on the dataset page: https://huggingface.co/datasets/reloading0101/threat-intelligence-dataset.FoldingTShirt_DualArxR5a_Samples
FoldingTShirt_DualArxR5a_Samples
100 real-robot teleoperation episodes for “Fold the T-shirt on the table.” on a DualArxR5a dual-arm robot. Format: raw MCAP (ROS 2 / rosbag2).
Source
Collected with TeleXperience, IO-AI’s product for real-robot teleoperation and data collection. An operator drives the robot; TeleXperience writes time-aligned RGB, joint commands, joint states, gripper targets, and end-effector poses to MCAP.
Product page:… See the full description on the dataset page: https://huggingface.co/datasets/io-intelligence/FoldingTShirt_DualArxR5a_Samples.syntheticDocQA_artificial_intelligence_test
Dataset Description
This dataset is part of a topic-specific retrieval benchmark spanning multiple domains, which evaluates retrieval in more realistic industrial applications.
It includes documents about the Artificial Intelligence.
Data Collection
Thanks to a crawler (see below), we collected 1,000 PDFs from the Internet with the query ('artificial intelligence'). From these documents, we randomly sampled 1000 pages.
We associated these with 100 questions and answers… See the full description on the dataset page: https://huggingface.co/datasets/vidore/syntheticDocQA_artificial_intelligence_test.COMPASS-Policy-Alignment-Testbed-Dataset
COMPASS: A Framework for Evaluating Organization-Specific Policy Alignment in LLMs
This dataset evaluates how well Large Language Models (LLMs) follow organization-specific policies in realistic enterprise-style settings.
What is COMPASS?
COMPASS is a framework for evaluating policy alignment: given only an organization’s policy (e.g., allow/deny rules), it enables you to benchmark whether an LLM’s responses comply with that policy in structured, enterprise-like… See the full description on the dataset page: https://huggingface.co/datasets/AIM-Intelligence/COMPASS-Policy-Alignment-Testbed-Dataset.egoproactive-synth-annotations
EgoProactive synthetic proactive annotations
Everything produced by the annotation and synthesis pipelines for the AI Wearables Challenge 2026 EgoProactive
Dense timestamped proactive walkthroughs generated with the ambient agent
(orchestrator deepseek/deepseek-v4-flash-0731 + vision Qwen3.6-27B),
using the held-out-validated dense policy (setup-phase coverage, repetition-collapse,
fire-at-onset) and a -0.5s onset correction at chunk-binning.
set
clips
median events/clip… See the full description on the dataset page: https://huggingface.co/datasets/ambient-intelligence-labs/egoproactive-synth-annotations.docqa_artificial_intelligence_beirThis is a copy of https://huggingface.co/datasets/jinaai/docqa_artificial_intelligence reformatted into the BEIR format. For any further information like license, please refer to the original dataset.
Disclaimer
This dataset may contain publicly available images or text data. All data is provided for research and educational purposes only. If you are the rights holder of any content and have concerns regarding intellectual property or copyright, please contact us at "support-data… See the full description on the dataset page: https://huggingface.co/datasets/jinaai/docqa_artificial_intelligence_beir.hsh-amends-sample
HSH Amends — evaluation sample
5,076 rows drawn from a 18,657,314-row commercial dataset. Signed, and verifiable in about two minutes without contacting us.
This is a sample of a paid product. It is published so a data team can evaluate the real thing — the real schema, the real values, the real verification chain — before any conversation about licensing. It is not open data and it is not a free tier. Licence terms are below.
Run the checks
Colab notebook —… See the full description on the dataset page: https://huggingface.co/datasets/HSH-Intelligence/hsh-amends-sample.sim-physics-configIndustryInstruction_Artificial-Intelligence
IndustryInstruction: Artificial Intelligence
This repository contains the IndustryInstruction: Artificial Intelligence domain subset of BAAI/IndustryInstruction.
Refer to the parent dataset card for data construction, intended use, limitations,
and licensing details.
Citation
If you use this dataset in your work, please cite IndustryInstruction:
@misc{shi2024industryinstruction,
title = {IndustryInstruction},
author = {Xiaofeng Shi and Lulu Zhao and Hua… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/IndustryInstruction_Artificial-Intelligence.details_Omartificial-Intelligence-Space__al-baka-llama3-8b-experimental
Dataset Card for Evaluation run of Omartificial-Intelligence-Space/al-baka-llama3-8b-experimental
Dataset automatically created during the evaluation run of model Omartificial-Intelligence-Space/al-baka-llama3-8b-experimental.
The dataset is composed of 136 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the… See the full description on the dataset page: https://huggingface.co/datasets/OALL/details_Omartificial-Intelligence-Space__al-baka-llama3-8b-experimental.url-intelligence-benchmark
📊 URL Intelligence Benchmark
Public, reproducible evaluation for URL intelligence agents, MCP servers and web analysis tools.
The URL Intelligence Benchmark is maintained with the open-source URL Intelligence Agent project by Vincenzo Picciuolo / HRN Innovation Technologies Ltd.
It is an evaluation asset, not a training corpus and not a scraped web dump.
Dataset configurations
The dataset now contains two explicit tracks.… See the full description on the dataset page: https://huggingface.co/datasets/vpicciuolo/url-intelligence-benchmark.AItuber-Persona-Voices-JA
AItuber Persona Voices JA
195体のAITuberペルソナに対し、キャラクター設定に基づいた声質設計・セリフ生成・音声合成を行ったデータセットです。
概要
項目
値
ペルソナ数
195
総音声ファイル数
20,800 (参照音声195 + 発話20,600)
音声フォーマット
WAV, PCM 16-bit, 44.1kHz, mono
セリフカテゴリ
original, descriptive, emotional
言語
日本語
データ構造
各行は1つの音声ファイルに対応し、以下のカラムを持ちます:
カラム
型
説明
persona_id
string
ペルソナ識別子 (persona_000 ~ persona_194)
persona_index
int
ペルソナインデックス（元データセットの行位置に対応）
persona_name
string
キャラクター名
voice_description_ja… See the full description on the dataset page: https://huggingface.co/datasets/kizuna-intelligence/AItuber-Persona-Voices-JA.egolongqa-synth-annotations
EgoLongQA synthetic MCQs, teacher traces and annotation outputs
Everything produced by the annotation and synthesis pipelines for the AI Wearables Challenge 2026
EgoLongQA ≤2B track, other than the distillation set (which lives in
infinitylogesh/egolongqa-junior-distill).
⚠️ Read this before counting rows
The synthetic set is 943 questions over 408 videos, and it is stored two ways:
file
rows
shape
training_sets/train_synth_v3.jsonl
943
flat — one row… See the full description on the dataset page: https://huggingface.co/datasets/ambient-intelligence-labs/egolongqa-synth-annotations.