SkepticalSam
Does LIMO prove that less is more in reasoning training?
LIMO: Less is More for Reasoning
Published: 12 May 2026 · Updated: 13 July 2026
Read the original sourceWhat the paper says
LIMO trains models with a sparse reward function that encourages succinct reasoning steps rather than verbose chain-of-thought. The authors claim that shorter explanations lead to better generalization and reduced hallucination.
The Critique
The “less is more” claim is compelling but not convincingly demonstrated. The paper reports marginal improvements on a few tasks and uses synthetic data. It also fails to discuss user needs; in some domains, longer reasoning may aid trust.
Why It Matters
Controlling output length could mitigate safety risks by limiting the space of possible hallucinations and reducing compute costs.
What They Missed
There is no user study on whether shorter explanations are actually easier to validate. The authors also do not explore trade-offs between brevity and completeness.
The Big Question
How can we adapt reasoning length dynamically based on task complexity and user preferences?