Dataset · Hugging Face

ONE-Lab/LiveVQA-new

Name: LiveVQA-new
Creator: ONE-Lab
License: cc-by-nc-4.0
Keywords: task_categories:image-text-to-text, language:en, license:cc-by-nc-4.0, size_categories:100K<n<1M, modality:image, arxiv:2504.05288, region:us, multimodal, vqa, knowledge-updating, retrieval-augmented-generation, peft

LiveVQA 🏠 Project Page | 💻 GitHub | 📖 Paper LIVEVQA is a new dataset for visual knowledge seeking and updating, comprising 12 different categories, 28,488 visual entity and 107,138 cross-modality multi-hop reasoning questions. 🧠 Overview LIVEVQA is a benchmark dataset of over 107,000 samples designed to evaluate Multimodal Large Language Models (MLLMs) on up-to-date real-world visual information. Each sample pairs a recent image—collected from news, YouTube… See the full description on the dataset page: https://huggingface.co/datasets/ONE-Lab/LiveVQA-new.

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Author / organization	ONE-Lab
License (as declared)	cc-by-nc-4.0
Downloads	400 (as reported by Hugging Face)
Likes	1
Created	16 June 2025
Last updated at source	7 July 2025

multimodalvqaknowledge-updatingretrieval-augmented-generationpeft

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16 Oct 2026 Description: LiveVQA 🏠 Project Page | 💻 GitHub | 📖 Paper LIVEVQA is a new dataset for visual knowledge seeking and updating, comprising 12 different categories, 28,488 visual entity and 107,138 cross-modality multi-hop reasoning questions. 🧠 Overvie → LiveVQA 🏠 Project Page | 💻 GitHub | 📖 Paper LIVEVQA is a new dataset for visual knowledge seeking and updating, comprising 12 different categories, 28,488 visual entity and 107,138 cross-modality multi-hop reasoning questions. 🧠 Overvie

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