Author

Pengfei Yang

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Preprint Aug 2026

LLM4LLM: Bridging Kernel Benchmarks and Real Deployment via Closed-Loop Agentic Optimization

LLM4LLM is introduced, a deployment-aware closed-loop optimization framework that starts from a target inference script, extracts phase-aware optimization tasks, searches with an experience-guided episodic agent, and accepts patches through in-model validation.

Hui Zeng, Pengfei Yang, Yanxin Chen et al. · 0 citations