Author

L. Ruis

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#machine learning Preprint Sep 2026

Legibility is Not Interpretability: Comparing Judged and Actual Importance in Chain-Of-Thought Reasoning

This work operationalizes the importance of a reasoning step as its advantage: the change in expected reward, e.g., producing the correct final answer, from including that step, estimated via Monte Carlo rollouts, and evaluates whether LLM judges can identify high-advantage steps and finds that sufficiently capable LLM...

Kevin Du, A. Hoyle, L. Ruis et al. · 0 citations

Preprint Jul 2026

Position: It's Time to Optimize LLMs for Self-Consistency

This position paper observes that a wide variety of techniques designed to improve specific aspects of LM behavior-targeting properties as diverse as adversarial robustness and factual coherence-can be understood as special cases of a common "consistency optimization" procedure and addressed with a standard set of opti...

Itamar Hagay Pres, Belinda Z. Li, L. Ruis et al. · 2 citations