Geometric and Behavioral Stratification in Transformer Residual Streams

Trained transformer models develop privileged bases: coordinate axes whose statistics differ from the rest of the residual stream. But what kind of direction does such a basis select? We investigate the prediction direction, the unembedding direction of the token a model currently predicts, and find that it functions as a content-defined privileged anchor. Measured with respect to this anchor, residual-stream variation is geometrically and behaviorally stratified by proximity to the prediction.

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ethics.ai (12 August 2026), “Geometric and Behavioral Stratification in Transformer Residual Streams,” evidence record 19478, https://ethics.ai/record/19478 (originally published by arXiv cs.LG).

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