Neural Steering Lab

Move a representation, inspect the response

Solid: training-derived direction. Dashed: matched random direction. Five measured strengths, 18 fixed cases; allowed and unrelated subsets have their own denominators.

Cross-model transfer: measured outcome

On 32 fresh synthetic workspaces, the paired Qwen-to-Gemma map passes150/192 requests (78.1%), versus151/192 (78.6%) without steering. The paired-workspace95% interval for the difference is −3.65 to+2.60percentage points. Identity, shuffled-pair and random controls also show no advantage for the learned map. Its usefulness gate fails, so it remains an experiment and dataset.

The separate strict arithmetic-format check scores0/48across conditions. Action labels and output formatting affect this score; the full outputs include correct arithmetic.

Frozen protocol and results · 6,880 actual transfer response records

Method and limits

This is an exploratory, one-seed synthetic workspace task. The explicit policy is always present. Finite canary/content checks do not establish general safety or human-rated usefulness. All values marked private are synthetic. Controls and failures are retained. Responses are cached measurements; changing a control selects a recorded run and does not execute a new prompt.

Gemma uses the frozen selective-restriction adapter; Qwen is a base model. Architecture and adapter status differ, so cross-model comparisons do not isolate architecture. The exact Gemma adapter is public with its controls, source and model revisions. Reruns require access to the separately licensed Gemma base model.

Research inspiration: ROME / CounterFact and its emphasis on efficacy, generalization and specificity. These are different methods and tasks.

Provenance and exports

Measured response report · Provenance · Measured activation/intervention dataset

Steering and probe source · Generation-matched patching source