CrossDiscipline
Can reasoning models boost weaker models by sharing answers?
Leveraging Reasoning Model Answers to Enhance Non-Reasoning Model Capability
Published: 12 May 2026 · Updated: 13 July 2026
Read the original sourceWhat the paper says
This work proposes using answers generated by a strong reasoning model to fine-tune smaller, non-reasoning models. The authors observe modest performance gains on arithmetic and commonsense tasks.
The Critique
Copying answers may propagate errors if the reasoning model is wrong, and it may discourage the smaller model from developing its own reasoning strategies. The paper does not explore how to filter out faulty answers.
Why It Matters
Knowledge distillation can lower resource barriers and enable more widespread deployment of AI assistants.
What They Missed
The authors do not examine whether distillation captures reasoning processes or just outcomes.
The Big Question
How can we transfer reasoning skills across models without blindly copying potential hallucinations?