Beyond Repeated Sampling: Learning Search Policies for LLM Reasoning
A small concept generator is optimized with reinforcement learning so that its concepts maximize the downstream success of a larger, frozen answer generator, and can thus be trained into an effective, reusable search policy for a much larger one.
Ismail Labiad, M. Kowalski, Marc Schoenauer et al.
· 0 citations