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cs.AI2026
Heterogeneous Information-Bottleneck Coordination Graphs for Multi-Agent Reinforcement Learning
Wei Duan, Junyu Xuan, En Yu +2
Coordination graphs are a central abstraction in cooperative multi-agent reinforcement learning (MARL), yet existing sparse-graph learners lack a theoretically grounded mechanism t…
cs.AI2026
VGAS: Value-Guided Action-Chunk Selection for Few-Shot Vision-Language-Action Adaptation
Changhua Xu, En Yu, Junyu Xuan +1
Vision--Language--Action (VLA) models bridge multimodal reasoning with physical control, but adapting them to new tasks with scarce demonstrations remains unreliable. While fine-tu…
cs.AI2024
An Autonomous Non-monolithic Agent with Multi-mode Exploration based on Options Framework
JaeYoon Kim, Junyu Xuan, Christy Liang +1
Most exploration research on reinforcement learning (RL) has paid attention to `the way of exploration', which is `how to explore'. The other exploration research, `when to explore…