7 papers
AION: Aerial Indoor Object-Goal Navigation Using Dual-Policy Reinforcement Learning
Zichen Yan, Yuchen Hou, Shenao Wang +3
Object-Goal Navigation (ObjectNav) requires an agent to autonomously explore an unknown environment and navigate toward target objects specified by a semantic label. While prior wo…
VIPO: Value Function Inconsistency Penalized Offline Reinforcement Learning
Xuyang Chen, Keyu Yan, Guojian Wang +1
Offline reinforcement learning (RL) learns effective policies from pre-collected datasets, offering a practical solution for applications where online interactions are risky or cos…
StreamAgent: Towards Anticipatory Agents for Streaming Video Understanding
Haolin Yang, Feilong Tang, Lingxiao Zhao +10
Real-time streaming video understanding in domains such as autonomous driving and intelligent surveillance poses challenges beyond conventional offline video processing, requiring…
MacroNav: Multi-Task Context Representation Learning Enables Efficient Navigation in Unknown Environments
Kuankuan Sima, Longbin Tang, Zhenyu Yang +2
Autonomous navigation in unknown environments requires multi-scale spatial understanding that captures geometric details, topological connectivity, and global structure to support…
Target-Aligned Fusion for Decision-Sequence Learning under Dynamics Shift
Guojian Wang, Quinson Hon, Xuyang Chen +1
External trajectories can improve offline decision-sequence learning, but dynamics shift may make some source subsequences inconsistent with the target environment. We study how to…
Taming OOD Actions for Offline Reinforcement Learning: An Advantage-Based Approach
Xuyang Chen, Keyu Yan, Wenhan Cao +1
Offline reinforcement learning (RL) learns policies from fixed datasets without online interactions, but suffers from distribution shift, causing inaccurate evaluation and overesti…