2025
Real-World Offline Reinforcement Learning from Vision Language Model Feedback
IROS 2025
Offline reinforcement learning can enable policy learning from pre-collected, sub-optimal datasets without online interactions. This makes it ideal for real-world robots and safety-critical scenarios, where collecting online data or expert demonstrations is slow, costly, and risky. However, most exi