Ruiqing Zhang

CRISP: Critical Step Perception for Training Efficient Deep Search Agents

This paper proposes CRISP, a framework for training efficient deep search agents through critical step perception that distinguishes interactions that gather necessary evidence from redundant ones and shapes the training reward to preserve the former while pruning the latter, improving efficiency without sacrificing the evidence needed for correct answers.