Preprint Open access
Giving Credit Where It's Due: Redundancy-Aware Learning for Efficient Reasoning
Large reasoning models can produce correct yet unnecessarily long reasoning traces. Existing methods improve reasoning efficiency with trajectory-level objectives or local token- and step-level signals, but rarely model inter-step semantic dependencies. This limits their ability to distinguish redundant steps from thos …