SARL trains search agents to recognize missing info without inference-time overhead
Taewhoo Lee · hf · 2026-10-29
A new paper proposes Self-Assessment Reinforcement Learning (SARL) to address poor search-state awareness in RAG search agents, which often hallucinate or terminate searches prematurely because they can't tell what information is still missing. SARL trains models to recognize their own search state during training, improving search efficiency without extra inference-time assessment.
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