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cs.CL2025
MUCAR: Benchmarking Multilingual Cross-Modal Ambiguity Resolution for Multimodal Large Language Models
Xiaolong Wang, Zhaolu Kang, Wangyuxuan Zhai +8
Multimodal Large Language Models (MLLMs) have demonstrated significant advances across numerous vision-language tasks. MLLMs have shown promising capability in aligning visual and…
cs.CL2025
Scaling External Knowledge Input Beyond Context Windows of LLMs via Multi-Agent Collaboration
Zijun Liu, Zhennan Wan, Peng Li +3
With the rapid advancement of post-training techniques for reasoning and information seeking, large language models (LLMs) can incorporate a large quantity of retrieved knowledge t…
cs.CL2025
Thinking with Visual Abstract: Enhancing Multimodal Reasoning via Visual Abstraction
Dairu Liu, Ziyue Wang, Minyuan Ruan +4
Images usually convey richer detail than text, but often include redundant information, which potentially downgrades multimodal reasoning performance. When faced with lengthy or co…