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cs.LG2026
Beyond Conservatism: Recoverability-Conditioned Exploration for Model-Based Imitation Learning
Xuanlin Chen, Ziyue Wang, Xunlan Zhou +3
Model-based imitation learning (MBIL) improves real-environment interaction efficiency by optimizing policies on imagined rollouts from a learned world model. However, the gap betw…
cs.LG2026
SAMBAR: Selective Anchoring via Method of Multipliers for Balanced Knowledge Acquisition and Retention in Vision-Language-Action Models
Aayushi Shrivastava, Xunlan Zhou, Hongrui Zhao +2
Vision-Language-Action (VLA) models leverage large-scale pretraining to ultimately achieve generalist manipulation. Deployed VLA policies must support continual learning to acquire…
cs.LG2026
BRICKS-WM: Building Reusability via Interface Composition Kinetics for Structured World Models
Shaowei Zhang, Jiahan Cao, Xunlan Zhou +2
Model-based Reinforcement Learning (MBRL) has achieved remarkable success in continuous control by leveraging latent world models. However, prevailing approaches typically rely on…