| name | steering-block-selection |
| description | How to choose where (and how many sites) to intervene for any operation on internal representations — activation patching, steering, CAA, DAS, SAE feature scaling, attribution patching. Use whenever the plan declares a target block / layer / site, especially when it hard-codes a single index (`target_block: 4`, `layer: 16`) without justification or copied from another paper. Covers picking the site by screening (gradient / attribution, or an activation signal) and by heuristic (mid-to-late layers usually steer best; widen to 3–5 layers if one is inert; sweep the stack at spaced intervals), and which component to target (attention / MLP / residual stream — circuit discovery studies attention heads + MLP). Prevents two symmetric failures: too few sites → downstream norm/attention denoise it → false "no effect"; too many → off-distribution collapse and the localization claim becomes untestable. Triggers include `target_block = 4`, `sliding window = 15`, `layer ∈ [12,18]`, `early blocks (0-7)`, "steering had no effect" while the same coefficient at a window did. |
Steering Block / Layer Selection
The point
Where and how many sites you intervene on changes both the effective strength of the intervention and whether a localization claim is testable.
- Too few (single site on a deep stack) → downstream norm/attention denoise it → looks like "no effect".
- Too many (whole stack) → off-distribution collapse → the effect is collapse-driven and no longer localized.
Choosing where to intervene
Pick the site(s) by a screening method, by heuristic, or both.
By method (pre-screen the layers):
- Gradient-based — rank layers by gradient / attribution score w.r.t. the target.
- Activation-based — rank by an activation signal (probe accuracy, diff-mean magnitude, separability).
By heuristic:
- Mid-to-late layers usually work best — start there.
- If a single layer shows no effect, intervene on 3–5 layers instead.
- To sweep the whole stack, use spaced intervals (e.g. every 2–3 layers) rather than every layer.
What to intervene on (transformer)
Target the attention, the MLP, or the residual stream — choose by what the claim is about.
Note: circuit discovery generally studies attention heads + MLP.
Two rules to keep it honest
- Match the claim. If the claim is about a region (e.g. "early layers 0–7"), intervene on a window covering that region and use matched windows elsewhere as null controls — a single site can't adjudicate a regional claim. Report the localization you actually observe; don't rewrite the claim to fit the data.
- Never copy a raw index across models of different depth. "Layer 16 of 32" → scale by relative depth (0.5 → layer 24 of 48), then check neighbors.
Composition
Lock the site set here first (the coefficient plateau is site-dependent), then sweep α via ../steering-coefficient-tuning/. Re-sweep the coefficient whenever the site set changes.
