GEMS: Geometric Constraints Enable Multi-Semantic Superposition in LLMs
Activation steering controls model behavior by modifying intermediate hidden states at inference time without retraining. Existing methods handle only single-direction injection; when multiple semantic directions are superposed without constraints, the model collapses. We show that this collapse decomposes into two independently acting sources: distributional deviation, where additive perturbations accumulate in norm across layers and drive activations outside the training distribution, and directional interference, where non-orthogonal semantic vectors mutually dampen when superposed. These two sources define the design constraints that any training-free multi-directional intervention mu...
| Authors | Yu Deng |
|---|---|
| Primary category | cs.CL |
| Published | 18 June 2026 |
| Last updated at source | 18 June 2026 |
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