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20242026
most citedMTVQA: Benchmarking Multilingual Text-Centric Visual Question Answering

5 citations · 7 across the 14 of their papers we have counts for

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5 papers · 1 filter

cs.CV2024

MovieBench: A Hierarchical Movie Level Dataset for Long Video Generation

Weijia Wu, Mingyu Liu, Zeyu Zhu +6

Recent advancements in video generation models, like Stable Video Diffusion, show promising results, but primarily focus on short, single-scene videos. These models struggle with g…

cs.CL2024

A Bounding Box is Worth One Token: Interleaving Layout and Text in a Large Language Model for Document Understanding

Jinghui Lu, Haiyang Yu, Yanjie Wang +9

Recently, many studies have demonstrated that exclusively incorporating OCR-derived text and spatial layouts with large language models (LLMs) can be highly effective for document…

cs.CV2024★ 1 cited

TabPedia: Towards Comprehensive Visual Table Understanding with Concept Synergy

Weichao Zhao, Hao Feng, Qi Liu +9

Tables contain factual and quantitative data accompanied by various structures and contents that pose challenges for machine comprehension. Previous methods generally design task-s…

cs.CV2024★ 5 cited

MTVQA: Benchmarking Multilingual Text-Centric Visual Question Answering

Jingqun Tang, Qi Liu, Yongjie Ye +14

Text-Centric Visual Question Answering (TEC-VQA) in its proper format not only facilitates human-machine interaction in text-centric visual environments but also serves as a de fac…

cs.CV2024★ 1 cited

TextSquare: Scaling up Text-Centric Visual Instruction Tuning

Jingqun Tang, Chunhui Lin, Zhen Zhao +15

Text-centric visual question answering (VQA) has made great strides with the development of Multimodal Large Language Models (MLLMs), yet open-source models still fall short of lea…