Search, Do not Guess: Teaching Small Language Models to Be Effective Search Agents

ArXi:2604.04651v1 Announce Type: new Agents equipped with search tools have emerged as effective solutions for knowledge-intensive tasks. While Large Language Models (LLMs) exhibit strong reasoning capabilities, their high computational cost limits practical deployment for search agents. Consequently, recent work has focused on distilling agentic behaviors from LLMs into Small Language Models (SLMs