Chen Lin

Structured Residual Adaptation for Multi-Task World Models

Multi-task model-based reinforcement learning (MBRL) typically relies on a single shared world model, but heterogeneity in task dynamics and physical properties often leads to brittle training and negative transfer. We propose Structured Residual Adaptation (SRA), a parameter-efficient approach that adapts a frozen wor...