AIBullisharXiv – CS AI · 10h ago6/10
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Enhancing LLM Problem Solving via Tutor-Student Multi-Agent Interaction
Researchers present PETITE, a tutor-student multi-agent framework that enhances LLM problem-solving by assigning complementary roles to agents from the same model. Evaluated on coding benchmarks, the approach achieves comparable or superior accuracy to existing methods while consuming significantly fewer tokens, demonstrating that structured role-differentiated interactions can improve LLM performance more efficiently than larger models or heterogeneous ensembles.