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Chain-of-thought (CoT) traces often serve as a proxy for how Large Language Models (LLMs) arrive at their answers. However, growing evidence shows that models'CoT often fails to reflect their internal computations and can be changed without affecting their final answers. In this work, we measure and improve the alignme...
The results suggest that for state-of-the-art LLMs, identifying a solution to the problem is insufficient, and reliably executing the resulting plan still poses a distinct challenge.
This work leverage Mixture of Factor Analyzers (MFA) as a scalable, unsupervised alternative that models the activation space as a collection of Gaussian regions with their local covariance structure, and positions local geometry, expressed through subspaces, as a promising unit of analysis for scalable concept discove...
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