datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
GenNOCSGUI-Xplore
GUI-Xplore Dataset 🖥️🔍
GUI-Xplore is a novel dataset designed to improve cross-application and cross-task generalization for GUI agents. It introduces exploration videos to provide context-aware learning, enabling agents to adapt to new applications efficiently.
📌 Dataset Summary
312 apps across 33 categories from 6 major domains (Entertainment, Productivity, Health, Shopping, Travel, News).
115+ hours of exploration videos, ensuring comprehensive app interaction… See the full description on the dataset page: https://huggingface.co/datasets/9211sun/GUI-Xplore.GUIOdyssey
Dataset Card for GUIOdyssey
Repository: https://github.com/OpenGVLab/GUI-Odyssey
Paper: https://arxiv.org/pdf/2406.08451
News⭐️
Latest version of GUIOdyssey released!🎉
This updated version features a larger dataset with 8,334 episodes, as well as richer semantic annotations. Compared to the previous version, we have added more fine-grained low-level instructions, image descriptions, action intentions, and context review for each step. Additionally, we provide bounding… See the full description on the dataset page: https://huggingface.co/datasets/hflqf88888/GUIOdyssey.GUI-360
GUI-360°: A Comprehensive Dataset And Benchmark For Computer-Using Agents
Paper | Code
GUI-360° is a large-scale, comprehensive dataset and benchmark suite designed to advance Computer-Using Agents (CUAs).
🎯 Key Features
🔢 1.2M+ executed action steps across thousands of trajectories
💼 Popular Windows office applications (Word, Excel, PowerPoint)
📸 Full-resolution screenshots with accessibility metadata
🎨 Multi-modal trajectories with reasoning traces
✅ Both… See the full description on the dataset page: https://huggingface.co/datasets/vyokky/GUI-360.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.jev-ai-api-guide-assetsGUI-Odyssey
Dataset Card for GUI Odyssey
News⭐️
A new and improved version of the GUIOdyssey dataset has been released! 🎉🎉
👉 Please use the latest version and refer to the updated README for the most up-to-date information.
We highly recommend using the new version for all training and evaluation!
Repository: https://github.com/OpenGVLab/GUI-Odyssey
Latest Version of Dataset: hflqf88888/GUIOdyssey
Paper: https://arxiv.org/pdf/2406.08451
Introduction
GUI Odyssey is… See the full description on the dataset page: https://huggingface.co/datasets/OpenGVLab/GUI-Odyssey.GUI-World
GUI-World: A Dataset for GUI-Orientated Multimodal Large Language Models
Dataset: GUI-World
Overview
GUI-World introduces a comprehensive benchmark for evaluating MLLMs in dynamic and complex GUI environments. It features extensive annotations covering six GUI scenarios and eight types of GUI-oriented questions. The dataset assesses state-of-the-art ImageLLMs and VideoLLMs, highlighting their limitations in handling dynamic and multi-step tasks. It provides… See the full description on the dataset page: https://huggingface.co/datasets/ONE-Lab/GUI-World.two-box-judge-gui
Two-Box Judge GUI Dataset
A multimodal dataset for training GUI element selection models. Given two candidate bounding boxes on a GUI screenshot, the model learns to select the one that better fulfills the user's intent.
Dataset Description
This dataset is designed for training judge models in GUI grounding pipelines. When a visual grounding model produces multiple candidate regions, the judge model determines which candidate best matches the user's command.… See the full description on the dataset page: https://huggingface.co/datasets/THU-BoZhang/two-box-judge-gui.Uni-GUI-Desktop-1
Uni-GUI-Desktop-1
A large-scale desktop GUI agent trajectory dataset, used as part of the training data for UI-MOPD (Multi-platform On-Policy Distillation for Continual GUI Agent Learning).
Dataset Statistics
Metric
Value
Trajectories
2,685
Total Steps
~36K
Platform
Desktop (1920x1080)
Applications
10 categories
Coordinate System
Normalized to [0, 999]
Applications
App
Description
chrome
Web browsing tasks
gimp… See the full description on the dataset page: https://huggingface.co/datasets/UI-MOPD/Uni-GUI-Desktop-1.go-swe-bench-v0
go_swe_bench v0 — real Go bug fixes, verified by the Go toolchain
246 tasks from 79 real Go repositories. Each task is a bug-fix commit whose co-committed test is red on the
parent and green on the fix. No LLM anywhere in the build.
Mined on 2026-09-19 from the GuildLM Go mining pipeline by inverting the filter that had thrown the tests
away (the pipeline was built for SFT data; a benchmark needs the opposite). Every task was verified twice
with go test: green at the commit (≥ 1… See the full description on the dataset page: https://huggingface.co/datasets/guildlm/go-swe-bench-v0.global-samplesreef-guidance-system
Dataset Card for Reef Guidance System
This dataset provides imagery used for training and evaluation of models in the Reef Guidance System. All imagery was collected by the Australian Institute of Marine Science using the ReefScan™ Transom Marine Monitoring System.
If you use this dataset in your work, please cite the associated paper: AI-driven dispensing of coral reseeding devices for broad-scale restoration of the Great Barrier Reef (citations provided at bottom of this… See the full description on the dataset page: https://huggingface.co/datasets/QCR-Underwater-Perception/reef-guidance-system.Guided-Lensless-Polarization-Imaging-stageI
Stage I reconstructions for evaluation (UPLight & ZJU-RGB-P)
This dataset accompanies Guided Lensless Polarization Imaging (CVPR 2026 Findings). It provides FISTA Stage-I outputs, RGB guidance images, and ground-truth polarization stacks for two public evaluation sets used in the paper.
Layout
UPLight (~1,991 scenes)
Folder
Description
UPLight/fista_grayscale/
3-channel grayscale polarization FISTA reconstructions
UPLight/fista_color/… See the full description on the dataset page: https://huggingface.co/datasets/noakraicer/Guided-Lensless-Polarization-Imaging-stageI.Long-Horizon-GUI-Datasetguildnouketsukejoudesugazangyouwaiyananodebosswosolotoubatsushiyoutoomoimasu
Bangumi Image Base of Guild No Uketsukejou Desu Ga, Zangyou Wa Iya Nanode Boss Wo Solo Toubatsu Shiyou To Omoimasu
This is the image base of bangumi Guild no Uketsukejou desu ga, Zangyou wa Iya nanode Boss wo Solo Toubatsu Shiyou to Omoimasu, we detected 64 characters, 4480 images in total. The full dataset is here.
Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual. If you intend to manually train models using this dataset, we… See the full description on the dataset page: https://huggingface.co/datasets/BangumiBase/guildnouketsukejoudesugazangyouwaiyananodebosswosolotoubatsushiyoutoomoimasu.GuiaVotos
GuiaVotos
Votos globales de la Guía de Zidane (reputación por perfil).
seed.json: conteo inicial importado de Supabase.
votes/*.json: un archivo por voto {p,d,f,ts}. El frontend suma seed + último voto por (navegador, perfil).
Anti-doble-voto: por navegador (localStorage). Sin garantía anti-spam: el token de escritura es público y limitado a este dataset.
Uni-GUI-OpenMobile
Uni-GUI-OpenMobile
A mobile GUI agent trajectory dataset collected on open-source Android applications via AndroidWorld, used as part of the training data for UI-MOPD (Multi-platform On-Policy Distillation for Continual GUI Agent Learning).
Dataset Statistics
Metric
Value
Trajectories
2,640
Total Steps
~25.9K
Platform
Android Mobile (1080x2400)
Applications
19 open-source apps
Coordinate System
Normalized to [0, 1000]… See the full description on the dataset page: https://huggingface.co/datasets/UI-MOPD/Uni-GUI-OpenMobile.isolated-guitar-chords
Isolated Guitar Chords Dataset
Overview
This dataset contains isolated guitar chord recordings designed for audio classification tasks such as chord recognition and real-time music analysis.
The data was intentionally recorded in realistic acoustic conditions, including minor background sounds, to improve robustness during inference in real-world environments.
Recording Setup
Instrument: 🎸 Fender FA-15 3/4 Acoustic Guitar
Recording method: Manual recording… See the full description on the dataset page: https://huggingface.co/datasets/severyn-k/isolated-guitar-chords.Gui-agent
Gui-Agent — GUI trajectories in LIBERO/VLA format
Human GUI demonstrations from four sources, unified into a single VLA-style
intermediate representation and written as LIBERO-layout HDF5, so LIBERO/VLA
dataloaders run against GUI data unchanged.
raw source ──[adapter]──> GuiEpisode ──[writer]──> LIBERO-style HDF5
per-source the IR format- what you train on
only specific
25,872 episodes / 453,264 steps / 235 GB… See the full description on the dataset page: https://huggingface.co/datasets/Yushi123/Gui-agent.GUI-Net-1M
Check more details at how to use this dataset at our repo
GUI-Net-1M is the dataset we keep running the pipeline introduced from TongUI paper.
Due to large file size, we have to split image files into parts. To do the extraction of images, please use the following script:
#!/bin/bash
# Directory containing the split files
SPLIT_DIR="/mnt/bofeidisk2/tmp/baidu_experience_full/images/split_parts_baidu_experience"
OUTPUT_DIR="merged_files"
# Create output directory if it doesn't… See the full description on the dataset page: https://huggingface.co/datasets/Bofeee5675/GUI-Net-1M.guidelines
🎉 NEW DROP 🎉 PubMed Guidelines
We just added 1627 clinical guidelines found in PubMed and PubMed Central to the dataset on December 23rd, 2023. Merry Christmas!
Clinical Guidelines
The Clinical Guidelines corpus is a new dataset of 47K clinical practice guidelines from 17 high-quality online medical sources. This dataset serves as a crucial component of the original training corpus of the Meditron Large Language Model (LLM). We publicly release a subset of 37K articles… See the full description on the dataset page: https://huggingface.co/datasets/epfl-llm/guidelines.GUI_BASED_PLATFORMgui-odyssey-train
Dataset Card for GUI Odyssey (Train Split)
⬆️ Test split shown above, but this also represents the train split.
This is a FiftyOne dataset with 89365 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("Voxel51/gui-odyssey-train")
# Launch… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/gui-odyssey-train.gui-agent-outputgui-odyssey-test
Dataset Card for GUI Odyssey (Test Split)
This is a FiftyOne dataset with 29426 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("Voxel51/gui-odyssey-test")
# Launch the App
session = fo.launch_app(dataset)
Dataset Details… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/gui-odyssey-test.GUI-Net-1M-extendedtransition_data_v1
GUI World Model — Branch Transitions
(s, a, s') transitions taken beside a walked trajectory rather than along
it: the same state, a different action, and the screen that actually followed.
Every state is captured from a running Ubuntu desktop — a screenshot, the
accessibility tree as XML, and the rendered element table the model reads.
A spine records what an agent did. This set records what it did not do and
what would have happened, which is the question an agent asks a world… See the full description on the dataset page: https://huggingface.co/datasets/gui-wm/transition_data_v1.ATO-Australian-Tax-Rulings-and-Guidance
ATO Rulings & Guidance — Australian Tax Law, Structured for AI
67,000+ Australian Taxation Office documents as RAG-ready NDJSON/CSV — Edited Private Advice, public rulings and determinations, ATO Interpretative Decisions, practical compliance guidelines, taxpayer alerts, decision impact statements, practice statements and legislative instruments. Every document parsed into structured, typed fields for legal RAG, LLM fine-tuning, and tax research automation.
Machine-readable… See the full description on the dataset page: https://huggingface.co/datasets/simplelex/ATO-Australian-Tax-Rulings-and-Guidance.guiact_smartphone_test
GUIAct Smartphone Dataset - Test Split
This is a FiftyOne dataset with 2079 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("Voxel51/guiact_smartphone_test")
# Launch the App
session = fo.launch_app(dataset)
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/guiact_smartphone_test.