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cs.CV2026
Seeing or Knowing? Visual Context Sensitivity in Multimodal Large Language Models
Jiaang Li, Chengzu Li, Zhaochong An +4
Multimodal Large Language Models (MLLMs) achieve strong performance by integrating visual inputs with the rich priors of pretrained language models. However, they often fail on vis…
cs.CV2026★ 2 cited
Video Understanding: From Geometry and Semantics to Unified Models
Zhaochong An, Zirui Li, Mingqiao Ye +9
Video understanding aims to enable models to perceive, reason about, and interact with the dynamic visual world. In contrast to image understanding, video understanding inherently…
cs.LG2026
Thinking in Frames: How Visual Context and Test-Time Scaling Empower Video Reasoning
Chengzu Li, Zanyi Wang, Jiaang Li +9
Vision-Language Models have excelled at textual reasoning, but they often struggle with fine-grained spatial understanding and continuous action planning, failing to simulate the d…