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cs.CV2026
ConFoThinking: Consolidated Focused Attention Driven Thinking for Visual Question Answering
Zhaodong Wu, Haochen Xue, Qi Cao +5
Thinking with Images improves fine-grained VQA for MLLMs by emphasizing visual cues. However, tool-augmented methods depend on the capacity of grounding, which remains unreliable f…
cs.CV2025
Not There Yet: Evaluating Vision Language Models in Simulating the Visual Perception of People with Low Vision
Rosiana Natalie, Wenqian Xu, Ruei-Che Chang +2
Advances in vision language models (VLMs) have enabled the simulation of general human behavior through their reasoning and problem solving capabilities. However, prior research ha…