Yuyang Li

The paper introduces Adaptive Context Management (AdaCoM), an external context manager that uses reinforcement learning to improve the performance of frozen LLM agents on long-horizon tasks by intelligently managing and pruning accumulated context.

RASER introduces a family of cheap, router-based systems that selectively decide whether to perform expensive multi-hop retrieval, significantly reducing LLM token costs while maintaining state-of-the-art performance.

This paper studies how to scale robust robot policies by expanding physical domains in a recoverable way.