9 citations · 24 across the 19 of their papers we have counts for
7 papers · 1 filter
MCTBench: Multimodal Cognition towards Text-Rich Visual Scenes Benchmark
Bin Shan, Xiang Fei, Wei Shi +6
The comprehension of text-rich visual scenes has become a focal point for evaluating Multi-modal Large Language Models (MLLMs) due to their widespread applications. Current benchma…
ParGo: Bridging Vision-Language with Partial and Global Views
An-Lan Wang, Bin Shan, Wei Shi +7
This work presents ParGo, a novel Partial-Global projector designed to connect the vision and language modalities for Multimodal Large Language Models (MLLMs). Unlike previous work…
Harmonizing Visual Text Comprehension and Generation
Zhen Zhao, Jingqun Tang, Binghong Wu +7
In this work, we present TextHarmony, a unified and versatile multimodal generative model proficient in comprehending and generating visual text. Simultaneously generating images a…
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…
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…
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…
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…