Zhan, Bihao

Reinforced Interactive Continual Learning via Real-time Noisy Human Feedback

2025 · arXiv (Cornell University)

This paper introduces an interactive continual learning paradigm where AI models dynamically learn new skills from real-time human feedback while retaining prior knowledge. This paradigm distinctively addresses two major limitations of traditional continual learning: (1) …