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All datasets matching “Path”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.