We propose AdaReasoner, a reinforcement learning–based framework that adaptively tunes LLM reasoning settings in few-shot scenarios, achieving gains in multiple experimental settings.

We propose Adaptive Reasoning Model (ARM), a reasoning model capable of adaptively selecting appropriate reasoning formats based on the task at hand.