AIBullisharXiv โ CS AI ยท Mar 177/10
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POLCA: Stochastic Generative Optimization with LLM
Researchers introduce POLCA (Prioritized Optimization with Local Contextual Aggregation), a new framework that uses large language models as optimizers for complex systems like AI agents and code generation. The method addresses stochastic optimization challenges through priority queuing and meta-learning, demonstrating superior performance across multiple benchmarks including agent optimization and CUDA kernel generation.