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cs.CV2026
Be Consistent! Enhancing Robust Visual Reasoning in LVLMs with Consistency Constraints
Liqiang Jing, Xiong Zhou, Siddharth Varia +3
While Large Vision-Language Models (LVLMs) exhibit strong perceptual capabilities, they remain vulnerable in visual reasoning tasks. Existing benchmarks largely focus on symbolic m…
cs.CV2024★ 1 cited
ViGoR: Improving Visual Grounding of Large Vision Language Models with Fine-Grained Reward Modeling
Siming Yan, Min Bai, Weifeng Chen +3
By combining natural language understanding, generation capabilities, and breadth of knowledge of large language models with image perception, recent large vision language models (…
cs.CV2024★ 1 cited
AffordanceLLM: Grounding Affordance from Vision Language Models
Shengyi Qian, Weifeng Chen, Min Bai +3
Affordance grounding refers to the task of finding the area of an object with which one can interact. It is a fundamental but challenging task, as a successful solution requires th…