1 citations · 1 across the 6 of their papers we have counts for
7 papers
Mosaic: Multi-Session Agentic Reinforcement Learning
Yilong Xu, Minrui Xu, Xinyu Zhou +3
Most existing agentic reinforcement learning methods assume single-session trajectories, where interaction proceeds within one continuously accumulated context. However, agentic te…
Unified Condition-Action Modeling for Accurate One-Step Action Generation
Xinyu Zhou, Zikun Cai, Kuangji Zuo +7
Robot manipulation requires policies that are both accurate and efficient, as robot control must respond to changing observations under tight latency constraints. Recent diffusion…
USS: Unifying Spatial-Semantic Prompting for End to End Embodied Visual Tracking
Yuchen Xie, Xinyu Zhou, Kuangji Zuo +4
Embodied Visual Tracking (EVT) requires an agent to continuously follow a designated target while moving through dynamic environments. Existing embodied tracking methods generally…
ATHENA: Accelerated Multi-Task Heterogeneous Influence Functions for Robot Data Curation
Tao Xu, Jiaxin Wang, Runhao Zhang +7
In robot imitation learning, influence functions provide a principled approach to quantify each demonstration's effect on robot task outcomes, yet scaling them to billion-parameter…
Gaze2Act: Gaze-Conditioned Vision-Language-Action Policies for Interactive Robot Manipulation
Kuangji Zuo, Gen Li, Bofan Lyu +9
Vision-Language-Action (VLA) models have recently shown strong potential for robot learning by following language instructions. However, in practice, language alone is often insuff…
A New Trajectory-Oriented Approach to Enhancing Comprehensive Crowd Navigation Performance
Xinyu Zhou, Songhao Piao, Chao Gao +1
Crowd navigation has garnered considerable research interest in recent years, especially with the proliferating application of deep reinforcement learning (DRL) techniques. Many st…
HeR-DRL:Heterogeneous Relational Deep Reinforcement Learning for Decentralized Multi-Robot Crowd Navigation
Xinyu Zhou, Songhao Piao, Wenzheng Chi +2
Crowd navigation has received significant research attention in recent years, especially DRL-based methods. While single-robot crowd scenarios have dominated research, they offer l…