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Lightweight proxy models cut LLM post-training costs while enabling cross-model signal reuse

Researchers propose Proxy-guided Update Signal Transfer, a post-training method that uses lightweight proxy models to discover optimization signals and transfer them to larger primary models, cutting computational overhead while enabling cross-model reuse.