GRASP: GRanularity-Aware Search Policy for Agentic RAG
GRASP is introduced, a reinforcement learning (RL) framework for training agents to adaptively coordinate complementary retrieval tools during multi-step reasoning, and it is suggested that learning to coordinate retrieval signals and context granularity is critical for agent's correct reasoning.