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cs.CV2026
InterTab: Interleaved Visual-Structure Alignment for Multi-Modal Table Reasoning
Hanqian Li, Sirui Huang, Chen Ling +12
Table images preserve structural information that are often lost in text serialization, and reasoning over them requires locating relevant rows, columns, and cells step by step. Cu…
cs.CV2026
Debias in Text, Believe Your Eyes: Text-Anchored Cross-Modal Transfer for Visual Counter-Commonsense Reasoning
Chen Ling, Hanqian Li, Dongnan Liu +9
The visual reasoning ability of multimodal large language models (MLLMs) is crucial for downstream applications, particularly counter-commonsense reasoning, which requires models t…
cs.CV2026
Seeing vs. Believing: Evaluating the Language Bias of Open-Source MLLMs in Counter-Intuitive Scenes
Chen Ling, Tongwei Zhang, Hanqian Li +1
Multimodal Large Language Models (MLLMs) have demonstrated remarkable performance in mainstream visual understanding tasks, but their ability to process action scenes that contradi…