Manifold steering along activation geometry induces behavioral trajectories matching the natural manifold of outputs, while linear steering produces off-manifold unnatural behaviors.
Dynamics of transient structure in in-context linear regression transformers
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In a controlled synthetic setting, transformers implement in-distribution task inference via convex combinations of task vectors and out-of-distribution inference via nearly orthogonal extrapolative representations.
Temporal diversity in task distribution during training increases generalization bias over memorization in transformers for in-context linear regression.
Small transformers on HMM prediction tasks exhibit correlated scaling between performance and linear encoding of belief distributions in residual activations.
This review synthesizes representative advances in high-dimensional statistics, highlights common themes and open problems, and points to key entry works.
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High-Dimensional Statistics: Reflections on Progress and Open Problems
This review synthesizes representative advances in high-dimensional statistics, highlights common themes and open problems, and points to key entry works.