Behavioral Entanglement in Transformers: Grassmann Geometry of Rho-Guided Supervised Fine-Tuning

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Authors: Bryan Sanchez
Cited by: 0

Abstract

We track behavioral subspaces throughout rho-guided SFT on Qwen 2.5-7B-Instruct under three protection conditions (gamma=0.03, gamma=0.10, anneal). The central finding is that surgery operates by compression, not rotation: pairwise Grassmann angles remain within 2-3 degrees of baseline across all conditions and layers, while effective dimensionality of target behaviors compresses 40-60% within the first 25 training steps. The protection strength gamma controls collateral compression: at gamma=0.10, factual dimensionality collapses to 1 at all layers, explaining weaker behavioral outcomes despite stronger protection. Compression is irreversible once established.

Fields of Study & Subjects

Topic Modeling Domain Adaptation and Few-Shot Learning Advanced Neural Network Applications

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
4 March 2026
Language
EN
Document type
Preprint