datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
VLADBenchgpt-edit-simplerRecap-DataComp-1B
Dataset Card for Recap-DataComp-1B
Recap-DataComp-1B is a large-scale image-text dataset that has been recaptioned using an advanced LLaVA-1.5-LLaMA3-8B model to enhance the alignment and detail of textual descriptions.
Dataset Details
Dataset Description
Our paper aims to bridge this community effort, leveraging the powerful and open-sourced LLaMA-3, a GPT-4 level LLM.
Our recaptioning pipeline is simple: first, we fine-tune a LLaMA-3-8B powered… See the full description on the dataset page: https://huggingface.co/datasets/UCSC-VLAA/Recap-DataComp-1B.collected_demos_trainingGPT-Image-Edit-1.5M
GPT-Image-Edit-1.5M A Million-Scale, GPT-Generated Image Dataset
📃Arxiv | 🌐 Project Page | 💻Github
GPT-Image-Edit-1.5M is a comprehensive image editing dataset that is built upon HQ-Edit, UltraEdit, OmniEdit and Complex-Edit, with all output images regenerated with GPT-Image-1.
📣 News
[2025.08.20] 🚀 We provide a script for multi-process downloading. See Multi-process Download.
[2025.07.27] 🤗 We release GPT-Image-Edit, a state-of-the-art image editing model with… See the full description on the dataset page: https://huggingface.co/datasets/UCSC-VLAA/GPT-Image-Edit-1.5M.HQ-Edit
Dataset Card for HQ-EDIT
HQ-Edit, a high-quality instruction-based image editing dataset with total 197,350 edits. Unlike prior approaches relying on attribute guidance or human feedback on building datasets, we devise a scalable data collection pipeline leveraging advanced foundation models, namely GPT-4V and DALL-E 3.
HQ-Edit’s high-resolution images, rich in detail and accompanied by comprehensive editing prompts, substantially enhance the capabilities of existing image editing… See the full description on the dataset page: https://huggingface.co/datasets/UCSC-VLAA/HQ-Edit.vlm_evaluation_v1.0
Datacard
This dataset is the evaluation VLM dataset used in VLABench. It is designed to evaluate the planning capabilities of Vision-Language Models (VLMs) in embodied scenarios.
Source
Project Page: https://vlabench.github.io/
Arxiv Paper: https://arxiv.org/abs/2412.18194
Code: https://github.com/OpenMOSS/VLABench
Uses
The dataset structure is as follows:
vlm_evaluation_v1.0/
├── CommenSence/
├── add_condiment_common_sense/
├──… See the full description on the dataset page: https://huggingface.co/datasets/VLABench/vlm_evaluation_v1.0.CADFS
CADFS Dataset
CADFS: A Big CAD Program Dataset and Framework for Computer-Aided Design with Large Language Models
🚀 Project Page
📃 Paper
💻 Code
🤗 Model
A large-scale dataset for parametric CAD model generation from text descriptions and multi-view images. Models are represented as FeatureScript programs, enabling direct import into Onshape environment.
This dataset was used to train and evaluate CADFS-2B, a fine-tuned Qwen2-VL-2B multimodal language model… See the full description on the dataset page: https://huggingface.co/datasets/VladPyatov/CADFS.vlabench_primitive_ft_lerobotVLA_Arena_L0_L_lerobot_openpi
VLA-Arena Dataset (L0 - Large Variant)
About VLA-Arena
VLA-Arena is an open-source benchmark designed for the systematic evaluation of Vision-Language-Action (VLA) models. It provides a complete and unified toolchain covering scene modeling, demonstration collection, model training, and evaluation. Featuring 150+ tasks across 11 specialized suites, VLA-Arena assesses models through hierarchical difficulty levels (L0-L2) to ensure comprehensive metrics for safety… See the full description on the dataset page: https://huggingface.co/datasets/VLA-Arena/VLA_Arena_L0_L_lerobot_openpi.Complex-Edit
Complex-Edit: CoT-Like Instruction Generation for Complexity-Controllable Image Editing Benchmark
📃Arxiv | 🌐Project Page | 💻Github | 📚Dataset | 📄HF Paper
We introduce Complex-Edit, a comprehensive benchmark designed to systematically evaluate instruction-based image editing models across instructions of varying complexity. To develop this benchmark, we harness GPT-4o to automatically collect a diverse set of editing instructions at scale.
Our approach follows a well-structured… See the full description on the dataset page: https://huggingface.co/datasets/UCSC-VLAA/Complex-Edit.collected_demossurg-vla-datasetimagenet-w21-wds-dinov2VLAA-Thinking
SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models
🌐 Project Page
• 📄 Arxiv
• 💻 Code
🤗 VLAA-Thinker Family
• 🤔 VLAA-Thinking Dataset
🤗 VLAA-Thinker-Qwen2.5-3B
• 🤗 VLAA-Thinker-Qwen2.5-7B
Both VLAA-Thinker-Qwen2.5-3B and VLAA-Thinker-Qwen2.5-7Bachieve SOTA performance on OpenCompass Multimodal Reasoning Leaderboard as of April 7th, 2025.
Contents
Quick Start 🚀… See the full description on the dataset page: https://huggingface.co/datasets/UCSC-VLAA/VLAA-Thinking.vladatadeterm_lerobot_rgb_depth_vlars-all-objectsAssets from https://huggingface.co/datasets/nvidia/PhysicalAI-Robotics-Manipulation-Objects-Kitchen-MJCF
Please visit https://huggingface.co/datasets/nvidia/PhysicalAI-Robotics-Manipulation-Objects-Kitchen-MJCF for more information
MedTrinity-25M
Tutorial of using Medtrinity-25M
MedTrinity-25M, a comprehensive, large-scale multimodal dataset for medicine, covering over 25 million images across 10 modalities, with multigranular annotations for more than 65 diseases. These enriched annotations encompass both global textual information, such as disease/lesion type, modality, region-specific descriptions, and inter-regional relationships, as well as detailed local annotations for regions of interest (ROIs), including bounding… See the full description on the dataset page: https://huggingface.co/datasets/UCSC-VLAA/MedTrinity-25M.omnid_vlabench_dataset_v_0wm-latentcorr-vla-recoveryVLA_Arena_L1_L_lerobot_openpi
VLA-Arena Dataset (L1 - Large Variant)
About VLA-Arena
VLA-Arena is an open-source benchmark designed for the systematic evaluation of Vision-Language-Action (VLA) models. It provides a complete and unified toolchain covering scene modeling, demonstration collection, model training, and evaluation. Featuring 150+ tasks across 11 specialized suites, VLA-Arena assesses models through hierarchical difficulty levels (L0-L2) to ensure comprehensive metrics for safety… See the full description on the dataset page: https://huggingface.co/datasets/VLA-Arena/VLA_Arena_L1_L_lerobot_openpi.MedVLThinker-pmc_vqaCode: https://github.com/UCSC-VLAA/MedVLThinker
Project Page: https://ucsc-vlaa.github.io/MedVLThinker/
📊 Datasets
Available Datasets
Our project provides several curated datasets for medical vision-language understanding and training:
Dataset
Modality
Description
Download
MedVLThinker-m23k-tokenized
Text-only
Tokenized version of the m23k dataset
🤗 HF
MedVLThinker-pmc_vqa-gpt_4o_reasoning-tokenized
Image-Text
Tokenized PMC-VQA dataset with GPT-4o generated… See the full description on the dataset page: https://huggingface.co/datasets/UCSC-VLAA/MedVLThinker-pmc_vqa.vla0-context-trace-full-demo-datasetMedVLThinker-EvalCode: https://github.com/UCSC-VLAA/MedVLThinker
Project Page: https://ucsc-vlaa.github.io/MedVLThinker/
📊 Datasets
Available Datasets
Our project provides several curated datasets for medical vision-language understanding and training:
Dataset
Modality
Description
Download
MedVLThinker-m23k-tokenized
Text-only
Tokenized version of the m23k dataset
🤗 HF
MedVLThinker-pmc_vqa-gpt_4o_reasoning-tokenized
Image-Text
Tokenized PMC-VQA dataset with GPT-4o generated… See the full description on the dataset page: https://huggingface.co/datasets/UCSC-VLAA/MedVLThinker-Eval.lerobot_libero_viThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "panda",
"total_episodes": 1693,
"total_frames": 273465,
"total_tasks": 40,
"chunks_size": 1000,
"fps": 10.0,
"splits": {
"train": "0:1693"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4"… See the full description on the dataset page: https://huggingface.co/datasets/VLAIResearchLab/lerobot_libero_vi.imagesVLA_Arena_L0_L_lerobot_smolvla
VLA-Arena Dataset (L0 - Large Variant)
About VLA-Arena
VLA-Arena is an open-source benchmark designed for the systematic evaluation of Vision-Language-Action (VLA) models. It provides a complete and unified toolchain covering scene modeling, demonstration collection, model training, and evaluation. Featuring 150+ tasks across 11 specialized suites, VLA-Arena assesses models through hierarchical difficulty levels (L0-L2) to ensure comprehensive metrics for safety… See the full description on the dataset page: https://huggingface.co/datasets/VLA-Arena/VLA_Arena_L0_L_lerobot_smolvla.VLA_pick_and_place_processedgiga-vla