MARS: Multi-Agent Adaptive Reasoning with Socratic Guidance for Automated Prompt Optimization

arXiv — cs.CL•Thursday, November 13, 2025 at 5:00:00 AM

On November 13, 2025, researchers unveiled the MARS framework, which stands for Multi-Agent Adaptive Reasoning with Socratic Guidance, aimed at optimizing prompts for large language models (LLMs). Traditional Automated Prompt Optimization (APO) methods often rely on rigid templates, limiting their effectiveness. MARS introduces a dynamic system comprising five complementary agents that engage in Socratic-style dialogues to refine prompts iteratively. By framing the optimization as a Partially Observable Markov Decision Process (POMDP), MARS allows for adaptive prompt refinement based on real-time feedback. Extensive experiments across multiple datasets have shown that MARS outperforms existing APO methods in optimization performance, search efficiency, and interpretability. This advancement not only enhances the capabilities of LLMs but also opens new avenues for more effective AI interactions.

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