AI RESEARCH
POLCA: Stochastic Generative Optimization with LLM
arXiv CS.AI
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ArXi:2603.14769v1 Announce Type: cross Optimizing complex systems, ranging from LLM prompts to multi-turn agents, traditionally requires labor-intensive manual iteration. We formalize this challenge as a stochastic generative optimization problem where a generative language model acts as the optimizer, guided by numerical rewards and text feedback to discover the best system. We