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Forget static relevance labels – RRPO uses LLM feedback to train RAG rerankers, boosting generation quality without expensive human annotations.
Ditch the costly process supervision: EVOM trains LLMs to generate optimization code by treating solvers as deterministic reward functions, enabling zero-shot solver transfer and efficient adaptation.
