datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
turkey-all-universitiesCertainly! Here’s the dataset description in Markdown format:
All Universities in Turkey Dataset
Description
This dataset contains detailed information about various universities. Each record represents a single university and includes attributes such as the university's name, type, city, website, address, logo URL, and a button for accessing additional details. This data is typically extracted from a web page listing universities.
Fields
1. id… See the full description on the dataset page: https://huggingface.co/datasets/h8st6ptv/turkey-all-universities.MedXpertQA
Dataset Card for MedXpertQA
MedXpertQA is a highly challenging and comprehensive benchmark designed to evaluate expert-level medical knowledge and advanced reasoning capabilities. It features both text-based and multimodal question-answering tasks, with the multimodal subset leveraging structured clinical information alongside images.
Dataset Description
MedXpertQA comprises 4,460 questions spanning diverse medical specialties, tasks, body systems, and image types. It… See the full description on the dataset page: https://huggingface.co/datasets/TsinghuaC3I/MedXpertQA.VOST-TAS
[NeurIPS 2025] Tracking and Understanding Object Transformations
If you like our project, please give us a star ⭐ on GitHub for the latest update.
💡 Description
Dataset Visualizations: GitHub
Paper: arXiv:2511.04678
Project Page: tubelet-graph.github.io
Project Repository: GitHub
Point of Contact: Yihong Sun
📊 Dataset Overview
VOST-TAS (TrackAnyState) is an extended version of the VOST validation set with explicit transformation annotations for tracking and… See the full description on the dataset page: https://huggingface.co/datasets/yihongs/VOST-TAS.TextEdit
TextEdit: A High-Quality, Multi-Scenario Text Editing Benchmark for Generation Models
Danni Yang,
Sitao Chen,
Changyao Tian
If you find our work helpful, please give us a ⭐ or cite our paper. See the InternVL-U technical report appendix for more details.
🎉 News
[2026/03/06] TextEdit benchmark released.
[2026/03/06] Evaluation code and initial baselines released.
[2026/03/06] Leaderboard updated with latest models.
📖 Introduction… See the full description on the dataset page: https://huggingface.co/datasets/opencompass/TextEdit.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.tlott-digital-products
T. Lott Digital Products
Digital product files for T. Lott's online store.
Products
Audiobooks (MP3)
eBooks (PDF)
Software (ZIP)
Cover images (PNG)
Download URLs
Files can be downloaded directly:
https://huggingface.co/datasets/ziggylott/tlott-digital-products/resolve/main/{filepath}
tcga-brca-titan-idc-ilc
tcga-brca-titan-idc-ilc
1. Tổng quan
[CẦN ĐIỀN THỦ CÔNG: mục đích, ngữ cảnh tạo dataset]
Tổng số bản ghi (cộng tất cả manifest phát hiện được): 4228
Số manifest phát hiện được trong bộ nhớ: 3 (df, brca_df, full_df)
Repo HuggingFace: okbro1234/tcga-brca-titan-idc-ilc
2. Cấu trúc lưu trữ tại đích
/ # suy từ hàm `HfApi`
file.txt # suy từ hàm `HfApi`
lfs.bin # suy từ hàm `HfApi`
shard_{i}_of_5.bin # suy từ hàm `HfApi`
remote/file/path.h5 #… See the full description on the dataset page: https://huggingface.co/datasets/okbro1234/tcga-brca-titan-idc-ilc.cktformer-dataset
CircuitFormer Dataset
This dataset contains a collection of 33,889 analog circuit netlists, images, and metadata collected from 62 textbooks.
Directory Structure
The dataset is organized into the following flattened directories (no train/test subfolders):
images/: Circuit diagrams (PNG format).
metadata/: JSON files containing circuit descriptions, names, and source information.
netlists/: SPICE netlist files (.cir).
Index Files
The dataset uses JSONL (JSON… See the full description on the dataset page: https://huggingface.co/datasets/touhid314/cktformer-dataset.DRIFT-TL-Distill-4K
DRIFT-TL-Distill-4K Dataset
This dataset contains multimodal reasoning examples with images and step-by-step thinking processes.
Paper: Directional Reasoning Injection for Fine-Tuning MLLMs
Code/Project Page: https://github.com/WikiChao/DRIFT
Dataset Structure
Each example contains:
messages: Conversation between user and assistant with image references
images: Paths to associated images
Usage
from datasets import load_dataset
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/ChaoHuangCS/DRIFT-TL-Distill-4K.Lora_Cloud_Dataset_Test
VLM Safety Inspector (2B / 4B / 8B) Mac 端评测与闭环套件
VLM Safety Inspector (2B / 4B / 8B) Mac 端闭环评测包
本目录是一个完全自包含（Self-Contained）的独立评测套件，专门适配您的 Mac（Apple Silicon / MPS）目录布局。
本目录是一个完全独立、自包含（Self-Contained）的评测套件，专为在 Mac (Apple Silicon / MPS) 上运行。
一、Mac 端文件布局自动识别（针对您的 iild 结构）
一、核心架构与流水线
评测脚本已内置针对您 Mac 端 iild/ 目录结构的全自动路径解析器：
在本次评测中，整条上行与闭环流水线严格遵循您的设想：
上游双塔一致性（In-Domain Consistency）：
输入给 Planner 和 Inspector 的 150 个任务安全规则，已在 PC 端由纯 Legacy… See the full description on the dataset page: https://huggingface.co/datasets/lvesucces/Lora_Cloud_Dataset_Test.Reason-RFT-CoT-Dataset
🤗 Reason-RFT CoT Dateset
The full dataset used in our project "Reason-RFT: Reinforcement Fine-Tuning for Visual Reasoning".
⭐️ Project │ 🌎 Github │ 🔥 Models │ 📑 ArXiv │ 💬 WeChat
🤖 RoboBrain: Aim to Explore ReasonRFT Paradigm to Enhance RoboBrain's Embodied Reasoning Capabilities.
♣️ Quick Start
Please refer to Dataset Preparation
🔥 Overview
Visual reasoning abilities play a crucial role in understanding complex multimodal… See the full description on the dataset page: https://huggingface.co/datasets/tanhuajie2001/Reason-RFT-CoT-Dataset.FIG
ORIG: Multi-Modal Retrieval-Enhanced Image Generation
Large Multimodal Models (LMMs) have achieved remarkable progress in generating photorealistic and prompt-aligned images, but they often produce outputs that contradict verifiable knowledge, especially when prompts involve fine-grained attributes or time-sensitive events. Conventional retrieval-augmented approaches attempt to address this issue by introducing external information, yet they are fundamentally incapable of… See the full description on the dataset page: https://huggingface.co/datasets/TyangJN/FIG.transientangelo_datasetcad-technical-drawings
CAD Technical Drawings, Generated by Cadsy
Turn a STEP model into a labeled technical drawing automatically.
This sample was created with Cadsy from 3D models in the
Zero-to-CAD-100k dataset.
For every STEP model, Cadsy generated:
one drawing using an ASME-style profile;
one drawing using an ISO-style profile; and
structured bounding-box labels for every retained annotation.
That is 65 CAD models, 130 technical drawings and their labels, produced
through one repeatable… See the full description on the dataset page: https://huggingface.co/datasets/cadsy/cad-technical-drawings.TIR-Bench
TIR-Bench: A Comprehensive Benchmark for Agentic Thinking-with-Images Reasoning
Introduction:
TIR-Bench is a comprehensive benchmark designed to evaluate the "thinking-with-images" capabilities of Multimodal Large Language Models (MLLMs), addressing a gap left by existing benchmarks like Visual Search which only test basic operations. As models like OpenAI o3 begin to intelligently create and operate tools to transform images for problem-solving, TIR-Bench provides 13… See the full description on the dataset page: https://huggingface.co/datasets/Agents-X/TIR-Bench.TABench
TextAnchor-Bench (TABench)
📄 Paper Link: Q-Mask: Query-driven Causal Masks for Text Anchoring in OCR-Oriented Vision-Language Models
TABench evaluates whether a vision-language model can (i) accurately read the text within a specified region (Region-to-Text, R2T) and (ii) localize the region(s) corresponding to a given text query (Text-to-Region, T2R). It contains 5,450 queries in total with an exact 1:1 balance between the two tasks, defined over the same set of 973 core images.… See the full description on the dataset page: https://huggingface.co/datasets/loongwayX/TABench.terminal-bench-2-verified
Terminal-Bench 2.0 Verified: Instruction & Environment Fix Version
中文版本
We conducted a comprehensive review of the entire Terminal-Bench 2.0 dataset and identified various issues. Both GLM-5 and Step 3.5-Flash were evaluated using this verified version.
This modified version addresses environment and instruction issues we discovered in Terminal-Bench 2.0. It includes two types of fixes:
Environment Fixes: Updated Dockerfiles and instructions to support Claude Code Agent runtime… See the full description on the dataset page: https://huggingface.co/datasets/harithoppil/terminal-bench-2-verified.OmniVideo-Test
OmniVideo-Test
Official repository for OmniVideo-Test, the human-verified test set introduced in our paper: "OmniVideo-100K: A Dataset for Audio-Visual Reasoning through Structured Scripts and Evidence Chains".
This repository includes:
videos/: Raw video files.
test_505.jsonl: The test set containing 505 multiple-choice QA pairs, complete with task taxonomies, ground-truth answers, and options.
OmniVideo-Test serves as the evaluation companion to the OmniVideo-100K… See the full description on the dataset page: https://huggingface.co/datasets/MiG-NJU/OmniVideo-Test.sat-vl-sft-training-ready-v1
Dataset Summary
NuTonic/sat-bbox-metadata-sft-v1 is a metadata-first, procedural VLM SFT dataset built from an existing “sat-bbox” style dataset tree (Sentinel‑2 chips + per-tile JSON metadata sidecars, optionally paired Mapbox stills).
The goal is to create high-signal, production-shaped supervision for multimodal chat models:
Captioning for satellite chips
Grounding (bounding boxes in normalized coordinates) for land-cover regions
Class-focused captions and absence checks for… See the full description on the dataset page: https://huggingface.co/datasets/NuTonic/sat-vl-sft-training-ready-v1.TripVVT-10K
TripVVT-10K Dataset
News
2026.06: TripVVT has been accepted by ECCV 2026.
2026.04: The TripVVT paper is available on arXiv.
The project page is available at https://shaodingbao.github.io/TripVVT/.
TripVVT-10K is a large-scale dataset for in-the-wild Video Virtual Try-On (VVT). It contains 10,031 high-quality video samples with triplet supervision, covering upper-body garments, lower-body garments, and dresses.
TripVVT-10K is released together with the… See the full description on the dataset page: https://huggingface.co/datasets/TripVVT/TripVVT-10K.RSCC-RSEdit-Test-Split
RSCC-RSEdit-Test-Split
This directory contains the test split for RSCC-RSEdit dataset.
Directory Structure
RSCC-RSEdit-Test-Split/
├── images/ # Original images (676 PNG files)
├── masks/ # Original grayscale masks (338 PNG files)
│ └── [mask files with pixel values 0,1,2,3,4]
├── masks_colorful/ # Colorful RGBA visualization masks (338 PNG files)
│ └── [same filenames as masks/, but in RGBA format with colors]
├──… See the full description on the dataset page: https://huggingface.co/datasets/BiliSakura/RSCC-RSEdit-Test-Split.TAO-Amodal
TAO-Amodal Dataset
Official Source for Downloading the TAO-Amodal and TAO Dataset.
📙 Project Page | 💻 Code | 📎 Paper Link | ✏️ Citations
Contact: 🙋🏻♂️Cheng-Yen (Wesley) Hsieh
Dataset Description
Our dataset augments the TAO dataset with amodal bounding box annotations for fully invisible, out-of-frame, and occluded objects.
Note that this implies TAO-Amodal also includes modal segmentation masks (as visualized in the color overlays above).
Our… See the full description on the dataset page: https://huggingface.co/datasets/chengyenhsieh/TAO-Amodal.LLaVA-Med-60K-IM-text
LLaVA-Med-60K-IM-text
This dataset is a text format of llava_med_instruct_60k_inline_mention.json.
We built this dataset using the Meta-Llama-3-70B-Instruct, and the instruction we used is: Rewrite the question-answer pairs into a paragraph format (Do not use the words 'question' and 'answer' in your responses):.
PMC articles that failed to download are excluded.
Non-medical images (e.g., diagrams) are excluded in an automatic way.
Despite these efforts, this dataset is not… See the full description on the dataset page: https://huggingface.co/datasets/myeongkyunkang/LLaVA-Med-60K-IM-text.unified-agent-trajectories
Unified Benchmark Agent Trajectories
Dataset release: v2.1.1 (2026-09-18)Record format: unified-agent-sft-v1
A growing collection of benchmark agent execution trajectories converted into one
transparent, multimodal, tool-aware representation. These are complete recorded benchmark
runs—not ordinary chat transcripts—including benchmark tasks, model reasoning and answers,
tool calls, tool observations, runtime status, and benchmark scores when available. The
directory layout is… See the full description on the dataset page: https://huggingface.co/datasets/ChrisDing1105/unified-agent-trajectories.ArtiMuse-10K
ArtiMuse:
Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
[🌐 Project Page]
[🚀 Online Demo]
[💻 Code]
[📄 Paper]
[[🧩 Checkpoints: 🤗 Hugging Face | 🤖 ModelScope]]
🌟 Building upon on ArtiMuse, we introduce UniPercept, a comprehensive follow-up work that provides a meticulous study on perceptual-level image understanding. It spans Image Aesthetics Assessment (IAA), Image Quality Assessment (IQA), and Image Structure & Texture… See the full description on the dataset page: https://huggingface.co/datasets/Thunderbolt215215/ArtiMuse-10K.humans-top
humans.top — LIVE Global ranking of influential people (open dataset)
This dataset ranks real, named living people by global influence — e.g. #1
Donald Trump, #2 Xi Jinping, #3 Vladimir Putin, alongside figures like Elon Musk,
Narendra Modi and Lionel Messi. Every row is a person: their live influence
rank, a concise biography in 15 languages, and Wikidata / Wikipedia links.
Published from the website humans.top (.top is the
domain name).
Available on (identical CC0… See the full description on the dataset page: https://huggingface.co/datasets/dsfox/humans-top.traffic-sign-bench
Traffic Sign Bench
Official per-sign SUMO maps for TrafficRuleBench: real Moscow OSM
layouts, 25 signs, 2500 maps. Protocol size is
80 train + 20 test maps per sign.
Road geometry is derived from OpenStreetMap
© OpenStreetMap contributors and is released under ODbL 1.0.
Download
All scenes land under data/scenes/<sign>/<scene_id>/, which is what eval
expects:
huggingface-cli download emb-ai/traffic-sign-bench \
--repo-type dataset \… See the full description on the dataset page: https://huggingface.co/datasets/emb-ai/traffic-sign-bench.embodied-spatial-reasoning
Embodied Spatial Reasoning Tasks
Dataset Description
This dataset is part of the embodied-spatial-reasoning project, where the agent has to actively explore the environment to determine if certain spatial relationships hold true. The tasks involve spatial reasoning with various objects and scenes. Each task includes a query about the spatial relationships between objects within a scene, which the agent must verify through exploration.
Dataset Structure
The… See the full description on the dataset page: https://huggingface.co/datasets/thanhqt2002/embodied-spatial-reasoning.FloodNet_2021-Track_2_Dataset_HF
FloodNet: High Resolution Aerial Imagery Dataset for Post-Flood Scene Understanding
This is the HF-hosted version of FloodNet.
The FloodNet 2021: A High Resolution Aerial Imagery Dataset for Post-Flood Scene Understanding provides high-resolution UAS imageries with detailed semantic annotation regarding the damages. To advance the damage assessment process for post-disaster scenarios, the authors of the dataset presented a unique challenge considering classification, semantic… See the full description on the dataset page: https://huggingface.co/datasets/takara-ai/FloodNet_2021-Track_2_Dataset_HF.TestingDataset
SciReC: Diagnostic Evaluation of Relational Reasoning in Multimodal Scientific Conversations with Adaptive Interaction
This dataset contains multimodal question-answering examples grounded in
textbook figures. Records in the figure-grounded configurations are filtered to
include only examples whose referenced image files are present in this release.
Configurations
visual: 13791 figure-grounded visual questions with resolved images.
knowledge: 13501 caption/text-grounded… See the full description on the dataset page: https://huggingface.co/datasets/Naga1289/TestingDataset.