Morning Edition · Wednesday, June 24, 2026Published at 6:42 AM EDT · New York

New work examines whether reasoning distillation losses differ in weight space, not just accuracy

A paper asks whether offline RL objectives that transfer reasoning from large teachers to small students produce genuinely different models, beyond their downstream scores.

An arXiv paper on the weight-space geometry of offline reasoning training takes up a question the field usually skips. Offline reinforcement-learning (RL) objectives such as RFT, DFT, offline GRPO and DPO are widely used to distill reasonin…