5 papers · 1 filter
DTP: A Simple yet Effective Distracting Token Pruning Framework for Vision-Language Action Models
Chenyang Li, Jieyuan Liu, Bin Li +5
Vision-Language Action (VLA) models have shown remarkable progress in robotic manipulation by leveraging the powerful perception abilities of Vision-Language Models (VLMs) to under…
See the Forest and the Trees: A Synergistic Reasoning Framework for Knowledge-Based Visual Question Answering
Junjie Wang, Yunhan Tang, Yijie Wang +4
Multimodal Large Language Models (MLLMs) have pushed the frontiers of Knowledge-Based Visual Question Answering (KBVQA), yet their reasoning is fundamentally bottlenecked by a reli…
ReGraP-LLaVA: Reasoning enabled Graph-based Personalized Large Language and Vision Assistant
Yifan Xiang, Zhenxi Zhang, Bin Li +6
Multimodal Large Language Models have shown strong performance across multimodal tasks, and recent personalized MLLMs can recognize user-specific concepts and generate contextual c…
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…