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. The stratification holds in all eighteen models tested (dense and mixture-of-experts, 7B-120B, base and instruction-tuned). A narrow, scale-invariant prediction interface concentrates readout-relev...
| Authors | Nelson Guda |
|---|---|
| Primary category | cs.LG |
| Published | 12 August 2026 |
| Last updated at source | 19 August 2026 |
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