Dataset · Hugging Face

TIGER-Lab/ViRL39K

Name: ViRL39K
Creator: TIGER-Lab
License: mit
Keywords: task_categories:question-answering, task_categories:image-text-to-text, language:en, license:mit, modality:image, arxiv:2504.08837, region:us, training, Reinforcement Learning

1. Overview of ViRL39K ViRL39K (pronounced as "viral") provides a curated collection of 38,870 verifiable QAs for Vision-Language RL training. It is built on top of newly collected problems and existing datasets ( Llava-OneVision, R1-OneVision, MM-Eureka, MM-Math, M3CoT, DeepScaleR, MV-Math) through cleaning, reformatting, rephrasing and verification. ViRL39K lays the foundation for SoTA Vision-Language Reasoning Model VL-Rethinker. It has the following merits: high-quality… See the full description on the dataset page: https://huggingface.co/datasets/TIGER-Lab/ViRL39K.

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Author / organization	TIGER-Lab
License (as declared)	mit
Downloads	1.5K (as reported by Hugging Face)
Likes	42
Created	21 April 2025
Last updated at source	23 April 2025

trainingReinforcement Learning

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16 Oct 2026 Description: 1. Overview of ViRL39K ViRL39K (pronounced as "viral") provides a curated collection of 38,870 verifiable QAs for Vision-Language RL training. It is built on top of newly collected problems and existing datasets ( Llava-OneVision, R1-OneVis → 1. Overview of ViRL39K ViRL39K (pronounced as "viral") provides a curated collection of 38,870 verifiable QAs for Vision-Language RL training. It is built on top of newly collected problems and existing datasets ( Llava-OneVision, R1-OneVis

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