
NeurIPS, 2026 (* equal contribution, † equal advising)
Model-based RL (MBRL) demonstrates strong sample efficiency by leveraging the synthetic trajectories from the learned transition model. However, current MBRL lacks visual generalization when unseen visual input is given to the model, limiting further deployment. VIGOR achieves zero-shot generalization to unseen visual distractions while preserving high sample efficiency, building upon TD-MPC2 and DreamerV3, which are the most popular MBRL baselines.





