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E. Lubana

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#machine learning Preprint Sep 2026

Monitoring and Discovering Reward Hacking with Internal Representations during LLM Evaluations

This work finds that simple difference of means vectors coherently represent reward hacking in Kimi K3, GLM 5.2, and Qwen 3.8 Max, and provides evidence that simple, white-box methods can be used to scalably study and monitor reward hacking behaviors in frontier open source models.

Leon Bergen, Usha Bhalla, Andrew Lee et al. · 0 citations
Preprint Aug 2026

Forking Fast: Efficiently Estimating Uncertainty Dynamics in Text Generation

It is shown that when resampling many reasoning chains, uncertainty dynamics converge to stable patterns, and noise is largely an artifact of sampling rather than an LLM's sensitivity to each individual token or reasoning step.

Eric J. Bigelow, Amir Zur, Satchel Grant et al. · 2 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

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