AI RESEARCH
MASPOB: Bandit-Based Prompt Optimization for Multi-Agent Systems with Graph Neural Networks
arXiv CS.AI
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ArXi:2603.02630v2 Announce Type: replace-cross Large Language Models (LLMs) have achieved great success in many real-world applications, especially the one serving as the cognitive backbone of Multi-Agent Systems (MAS) to orchestrate complex workflows in practice. Since many deployment scenarios preclude MAS workflow modifications and its performance is highly sensitive to the input prompts, prompt optimization emerges as a natural approach to improve its performance.