datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
path-vqa
Dataset Card for PathVQA
Dataset Description
PathVQA is a dataset of question-answer pairs on pathology images. The dataset is intended to be used for training and testing
Medical Visual Question Answering (VQA) systems. The dataset includes both open-ended questions and binary "yes/no" questions.
The dataset is built from two publicly-available pathology textbooks: "Textbook of Pathology" and "Basic Pathology", and a
publicly-available digital library: "Pathology… See the full description on the dataset page: https://huggingface.co/datasets/flaviagiammarino/path-vqa.PathEval
PathEval: A Benchmark for Evaluating Vision-Language Models as Evaluators for Path Planning
Overview
Despite their promise to perform complex reasoning, large language models (LLMs) have been shown to have limited effectiveness in end-to-end planning. This has inspired an intriguing question: if these models cannot plan well, can they still contribute to the planning framework as a helpful plan evaluator? In this work, we generalize this question to consider LLMs… See the full description on the dataset page: https://huggingface.co/datasets/maghzal/PathEval.bridge_v2_lerobot_pathmask
PEEK VLM-Labeled BRIDGE_v2 dataset
This dataset contains the LeRobot-format BRIDGE-v2 dataset with paths and masks from the PEEK VLM drawn onto the image: PEEK: Guiding and Minimal Image Representations for Zero-Shot Generalization of Robot Manipulation Policies.
PEEK fine-tunes Vision-Language Models (VLMs) to predict a unified point-based intermediate representation for robot manipulation. This representation consists of:
End-effector paths: specifying what actions to take.… See the full description on the dataset page: https://huggingface.co/datasets/jesbu1/bridge_v2_lerobot_pathmask.Fino1_Reasoning_Path_FinQAFino1 is a financial reasoning dataset based on FinQA, with GPT-4o-generated reasoning paths to enhance structured financial question answering.
For more details, please check our paper arxiv.org/abs/2502.08127.
Source Data
Initial Data Collection and Normalization
The dataset originates from FinQA dataset.
Annotations
Annotation Process
We add a prompt and create a reasoning process using GPT-4o for each question-answer pair.
💡 Citation… See the full description on the dataset page: https://huggingface.co/datasets/TheFinAI/Fino1_Reasoning_Path_FinQA.PATHOS-PLM-EMBEDDINGS
PATHOS PLM Embeddings
Precomputed protein language model (PLM) embeddings for missense substitutions and wild-type residues in 20,416 human SwissProt proteins. These embeddings are used by PATHOS to predict the pathogenicity of missense mutations.
Paper: http://dx.doi.org/10.1016/j.ailsci.2026.100165
Dataset Structure
The repository contains two config families for each PLM:
Mutation configs: <model> stores embeddings for generated missense substitutions.
Wild-type… See the full description on the dataset page: https://huggingface.co/datasets/DSIMB/PATHOS-PLM-EMBEDDINGS.Patho-Bench
♆ Patho-Bench
📄 Preprint | Code
Patho-Bench is designed to evaluate patch and slide encoder foundation models for whole-slide images (WSIs).
This HuggingFace repository contains the data splits for the public Patho-Bench tasks. Please visit our codebase on GitHub for the full codebase and benchmark implementation.
This project was developed by the Mahmood Lab at Harvard Medical School and Brigham and Women's Hospital. This work was funded by NIH NIGMS R35GM138216.
[!NOTE]… See the full description on the dataset page: https://huggingface.co/datasets/MahmoodLab/Patho-Bench.indoor-anomaly-detection-path-obstruction-monitoring
Indoor Anomaly Detection & Path Obstruction Monitoring
Generated by datapack-import.ts
This dataset mirrors public data-pack render outputs from Physicl.
Each row represents one render view. The image column contains a stable URL to the primary render image uploaded under /data; image_path stores the relative repository path and data_commit_sha pins the Hugging Face dataset commit used by those URLs. Files are uploaded as downloaded unless optional PNG recompression is enabled… See the full description on the dataset page: https://huggingface.co/datasets/physicl/indoor-anomaly-detection-path-obstruction-monitoring.pathological_speech
Pathological Speech (TORGO + UA-Speech + LibriSpeech Normal)
Mixed-corpus speech dataset for training and evaluating controllable
speech-synthesis and severity-classification models. Three corpora are merged
with unified metadata so a single model can learn severity- and
gender-conditioned generation without confounds.
Splits (speaker-disjoint since 2026-09-14)
Split
Rows
Bytes (parquet)
What it is
train
37704
5,500,328,387
every clip of every speaker… See the full description on the dataset page: https://huggingface.co/datasets/resproj007/pathological_speech.plant-pathology-2021
Description
Dataset from the Plant Pathology 2021 (FGVC8) Challenge.
'
For Plant Pathology 2021-FGVC8, we have significantly increased the number of foliar disease images and added additional disease categories. This year’s dataset contains approximately 23,000 high-quality RGB images of apple foliar diseases, including a large expert-annotated disease dataset. This dataset reflects real field scenarios by representing non-homogeneous backgrounds of leaf images taken at different… See the full description on the dataset page: https://huggingface.co/datasets/timm/plant-pathology-2021.AIME_1983_2024-Reasoning-Paths
News
🌟🌟🌟 Try this dataset in our HuggingFace Space!
🥳🥳🥳 Thrilled to share that this NeurIPS paper was selected as 🏆 #1 Paper of the Day on Oct. 20th!
Sampled Reasoning Paths for the AIME dataset (from 1983 to 2024)
This dataset contains sampled reasoning paths for the AIME_1983_2024 dataset, released as part of the NeurIPS 2025 paper: "A Theoretical Study on Bridging Internal Probability and Self-Consistency for LLM Reasoning" (Arxiv).… See the full description on the dataset page: https://huggingface.co/datasets/WNJXYK/AIME_1983_2024-Reasoning-Paths.Alexandria_geometry_optimization_paths_PBE_2D
Cite this dataset Schmidt, J., Hoffmann, N., Wang, H., Borlido, P., Carriço, P. J. M. A., Cerqueira, T. F. T., Botti, S., and Marques, M. A. L. Alexandria geometry optimization paths PBE 2D. ColabFit, 2025. https://doi.org/10.60732/8781419f
This dataset has been curated and formatted for the ColabFit Exchange
This dataset is also available on the ColabFit Exchange:
https://materials.colabfit.org/id/DS_6pieq95jrqpn_0
Visit the ColabFit… See the full description on the dataset page: https://huggingface.co/datasets/colabfit/Alexandria_geometry_optimization_paths_PBE_2D.Alexandria_geometry_optimization_paths_PBE_3D
Cite this dataset Schmidt, J., Hoffmann, N., Wang, H., Borlido, P., Carriço, P. J. M. A., Cerqueira, T. F. T., Botti, S., and Marques, M. A. L. Alexandria geometry optimization paths PBE 3D. ColabFit, 2024. https://doi.org/10.60732/c88da7df
This dataset has been curated and formatted for the ColabFit Exchange
This dataset is also available on the ColabFit Exchange:
https://materials.colabfit.org/id/DS_s6gf4z2hcjqy_0
Visit the ColabFit… See the full description on the dataset page: https://huggingface.co/datasets/colabfit/Alexandria_geometry_optimization_paths_PBE_3D.PathGeneWithout the consent of Xiangya Hospital of Central South University or its Pathology Department, the use of the raw data is prohibited. Should any data be used for commercial purposes, we will hold the user legally accountable.
We support the following 21 pre-trained foundation models to extract the feature representation of WSI. Please contact us by email before using. (Strongly recommended!!)
🔨 1. Installation:
Create an environment: conda create -n "trident" python=3.10, and… See the full description on the dataset page: https://huggingface.co/datasets/LiangruiPan/PathGene.Breast_Pathology_Image_JPG
BreastPathDB
BreastPathDB is a breast cancer histopathology dataset for whole-slide image based subtype classification. It contains 770 de-identified whole-slide images, including 165 H&E slides and 605 IHC slides, with clinical subtype labels, curated metadata, and patient-level train/validation/test splits.
The dataset is intended for computational pathology benchmarking, weakly supervised WSI classification, and cross-cohort method development.
Browse files and metadata… See the full description on the dataset page: https://huggingface.co/datasets/kmmuleelab/Breast_Pathology_Image_JPG.libero_90_lerobot_pathmask_rdpThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "panda",
"total_episodes": 0,
"total_frames": 0,
"total_tasks": 0,
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"total_chunks": 0,
"chunks_size": 1000,
"fps": 20,
"splits": {},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/jesbu1/libero_90_lerobot_pathmask_rdp.bridge_v2_lerobot_15freq_pathmaskFino1_Reasoning_Path_FinQA_v2Fino1 is a financial reasoning dataset based on FinQA, with GPT-4o-generated reasoning paths to enhance structured financial question answering.
For more details, please check our paper arxiv.org/abs/2502.08127.
Source Data
Initial Data Collection and Normalization
The dataset originates from FinQA; TATQA, ConvFinQA, DocMath-Eval, DocFinQA, Bizbench dataset.
Annotations
Annotation Process
We add a prompt and create a reasoning process using GPT-4o… See the full description on the dataset page: https://huggingface.co/datasets/TheFinAI/Fino1_Reasoning_Path_FinQA_v2.pathereaPatherea: Cell Detection and Classification for the 2020s
📄 Citation
If you use this data or find it helpful, please cite our work:
@article{vstepec2024patherea,
title={Patherea: Cell Detection and Classification for the 2020s},
author={{\v{S}}tepec, Dejan and Jer{\v{s}}e, Maja and {\DJ}oki{\'c}, Sne{\v{z}}ana and Jeruc, Jera and Zidar, Nina and Sko{\v{c}}aj, Danijel},
journal={arXiv preprint arXiv:2412.16425},
year={2024}
}
📚 Read the paper on arXiv:… See the full description on the dataset page: https://huggingface.co/datasets/ds2268/patherea.Llama-slideQA-Sample-Featuresai-crawler-index
AI Crawler Index
150 web crawlers and AI user agents from 74 operators — what each one is for,
what blocking it costs you, and the IP ranges its operator publishes.
Plus a compiled user-agent regex and the union of 1997 IPv4 and 1062 IPv6
prefixes from 15 operator-published range files.
Home: https://www.pathwren.workers.dev/c/huggingface-datasets/ · CC0 · no signup, no key.
What this is, plainly
This is an independent, non-commercial automated project. It is run… See the full description on the dataset page: https://huggingface.co/datasets/pathwren/ai-crawler-index.PathoROB-camelyon
PathoROB
Preprint | Code | Licenses | Cite
PathoROB is a benchmark for the robustness of pathology foundation models (FMs) to non-biological medical center differences.
PathoROB contains four datasets covering 28 biological classes from 34 medical centers and three metrics:
Robustness Index: Measures the dominance of biological over non-biological features in an FM representation space.
Average Performance Drop (APD): Measures the robustness of downstream models to shortcut… See the full description on the dataset page: https://huggingface.co/datasets/bifold-pathomics/PathoROB-camelyon.STARC-912-Dec-2025 Note: The latest updated dataset will be available soon.
Paper link is given here: Openreview or Arxiv .
To learn more about dataset generation using DeepCluster++, see the detailed documentation here.
For training and validation of baseline and foundation classifier models using the generated dataset, visit here.
Both the collected dataset and the trained model have been made publicly available for research use. Visit here .
If you find our work useful in your research or use… See the full description on the dataset page: https://huggingface.co/datasets/Path2AI/STARC-9.PathoROB-tcga
PathoROB
Preprint | Code | Licenses | Cite
PathoROB is a benchmark for the robustness of pathology foundation models (FMs) to non-biological medical center differences.
PathoROB contains four datasets covering 28 biological classes from 34 medical centers and three metrics:
Robustness Index: Measures the dominance of biological over non-biological features in an FM representation space.
Average Performance Drop (APD): Measures the robustness of downstream models to shortcut… See the full description on the dataset page: https://huggingface.co/datasets/bifold-pathomics/PathoROB-tcga.Panda-Discordant-Pathology-ErrorsPathoROB-tolkach_esca
PathoROB
Preprint | Code | Licenses | Cite
PathoROB is a benchmark for the robustness of pathology foundation models (FMs) to non-biological medical center differences.
PathoROB contains four datasets covering 28 biological classes from 34 medical centers and three metrics:
Robustness Index: Measures the dominance of biological over non-biological features in an FM representation space.
Average Performance Drop (APD): Measures the robustness of downstream models to shortcut… See the full description on the dataset page: https://huggingface.co/datasets/bifold-pathomics/PathoROB-tolkach_esca.libero_90_lerobot_pathmask_rdp_full_path_maskThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.0",
"robot_type": "panda",
"total_episodes": 3953,
"total_frames": 574118,
"total_tasks": 73,
"total_videos": 0,
"total_chunks": 4,
"chunks_size": 1000,
"fps": 10,
"splits": {
"train": "0:3953"},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/jesbu1/libero_90_lerobot_pathmask_rdp_full_path_mask.drone-detection-dataset
Dataset Card for Drone Detection Dataset
This dataset card describes the processed version of the Drone Detection Dataset, originally curated by Maciej Pawełczyk and Marek Wojtyra, adapted to a COCO-style format for efficient usage in modern deep learning pipelines
Dataset Details
Dataset Description
The Drone Detection Dataset is a real-world object detection dataset for UAV detection tasks. It includes RGB images annotated with bounding boxes in the COCO… See the full description on the dataset page: https://huggingface.co/datasets/pathikg/drone-detection-dataset.wiki_erica_path_v9.1MLLM_pathPathMMUThis is the official Hugging Face repo for PathMMU: A Massive Multimodal Expert-Level Benchmark for Understanding and Reasoning in Pathology
🌐 Homepage | 🤗 Dataset | 📖 arXiv | GitHub
🔔News
Important Notes!!!!!!
The benchmark data and evaluation code have been released (8/7/2024)
Abstract
The emergence of large multimodal models has unlocked remarkable potential in AI, particularly in pathology. However, the lack of specialized, high-quality benchmark… See the full description on the dataset page: https://huggingface.co/datasets/jamessyx/PathMMU.