1 citations · 2 across the 4 of their papers we have counts for
4 papers
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…
Proposer-Agent-Evaluator(PAE): Autonomous Skill Discovery For Foundation Model Internet Agents
Yifei Zhou, Qianlan Yang, Kaixiang Lin +5
The vision of a broadly capable and goal-directed agent, such as an Internet-browsing agent in the digital world and a household humanoid in the physical world, has rapidly advance…
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 (…
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…