5 papers
ASearch: Ambiguity-Aware Question Answering with Reinforcement Learning
Fengji Zhang, Xinyao Niu, Chengyang Ying +7
Recent advances in Large Language Models (LLMs) and Reinforcement Learning (RL) have led to strong performance in open-domain question answering (QA). However, existing models stil…
Reinforced Embodied Active Defense: Exploiting Adaptive Interaction for Robust Visual Perception in Adversarial 3D Environments
Xiao Yang, Lingxuan Wu, Lizhong Wang +3
Adversarial attacks in 3D environments have emerged as a critical threat to the reliability of visual perception systems, particularly in safety-sensitive applications such as iden…
Self-Consistent Model-based Adaptation for Visual Reinforcement Learning
Xinning Zhou, Chengyang Ying, Yao Feng +2
Visual reinforcement learning agents typically face serious performance declines in real-world applications caused by visual distractions. Existing methods rely on fine-tuning the…
Exploratory Diffusion Model for Unsupervised Reinforcement Learning
Chengyang Ying, Huayu Chen, Xinning Zhou +3
Unsupervised reinforcement learning (URL) aims to pre-train agents by exploring diverse states or skills in reward-free environments, facilitating efficient adaptation to downstrea…
ManiBox: Enhancing Embodied Spatial Generalization via Scalable Simulation Data Generations
Hengkai Tan, Xuezhou Xu, Chengyang Ying +7
Embodied agents require robust spatial intelligence to execute precise real-world manipulations. However, this remains a significant challenge, as current methods often struggle to…