datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Chat2Workflow-Evaluation
Chat2Workflow
Chat2Workflow is a benchmark designed for evaluating the ability of Large Language Models (LLMs) to generate executable visual workflows from natural language instructions.
Paper: Chat2Workflow: A Benchmark for Generating Executable Visual Workflows with Natural Language
Repository: zjunlp/Chat2Workflow
Overview
Executable visual workflows are widely used in industrial deployments for their reliability and controllability. Chat2Workflow addresses the… See the full description on the dataset page: https://huggingface.co/datasets/zjunlp/Chat2Workflow-Evaluation.Medical_Multimodal_Evaluation_Data
Evaluation Guide
This dataset is used to evaluate medical multimodal LLMs, as used in HuatuoGPT-Vision. It includes benchmarks such as VQA-RAD, SLAKE, PathVQA, PMC-VQA, OmniMedVQA, and MMMU-Medical-Tracks.
To get started:
Download the dataset and extract the images.zip file.
Find evaluation code on our GitHub: HuatuoGPT-Vision.
This open-source release aims to simplify the evaluation of medical multimodal capabilities in large models. Please cite the relevant benchmark… See the full description on the dataset page: https://huggingface.co/datasets/FreedomIntelligence/Medical_Multimodal_Evaluation_Data.UGround-Offline-EvaluationPhysicalAI-US-Evaluation
PhysicalAI-US-Evaluation
A held-out US evaluation set for the navigation planner: 19,744 records, each pairing a single front-camera frame with the corresponding past trajectory, future ground-truth waypoints, and a natural-language driving objective.
Provenance
Every record here was drawn — uniformly at random — from the pool of US scenes that were withheld from every training stage of the planner:
the base VLA pretraining mix,
the reasoning supervised fine-tuning (SFT)… See the full description on the dataset page: https://huggingface.co/datasets/mjf-su/PhysicalAI-US-Evaluation.PhysicalAI-DE-Evaluation
PhysicalAI-DE-Evaluation
A held-out German evaluation set for the navigation planner: 19,999 records, each pairing a single front-camera frame with the corresponding past trajectory, future ground-truth waypoints, and a natural-language driving objective.
Provenance
Every record here was drawn from the pool of German scenes that were withheld from every training stage of the planner:
the base VLA pretraining mix,
the reasoning supervised fine-tuning (SFT) stage, and
the… See the full description on the dataset page: https://huggingface.co/datasets/mjf-su/PhysicalAI-DE-Evaluation.vla-evaluation-v3vla-evaluation-v4