Layer 31 · Neuron 3421 · suppressed

L31N3421-1

Word quirks:

“im”“ Im”“Im”“ im”“IM”“-im”“_im”“(im”

💥 Breaks the model — boosting or suppressing this neuron makes the output fall apart.

Identity (according to the specimen itself)

The reply didn't hold together

imimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimimim

Nearest neighbors

Specimens with similar replies or word quirks. Similarity runs from −1 to 1; 1 is identical. These are leads, not shared mechanisms. How profiles are built.

By word quirks Profile recipe

Specimen	Similarity	Word quirks
1. L29N7325+1🕒	0.99	“ im”“ Im”“Im”
2. L28N6008-1🕒	0.99	“im”“IM”“ IM”
3. L28N5465+1🕒	0.98	“ im”“_im”“'im”
4. L29N341+1🕒	0.98	“im”“ im”“'im”
5. L27N8867+1🕒	0.98	“ im”“ Im”“Im”
6. L29N1105+1🕒	0.97	“ im”“_im”“ Im”
7. L26N7815-1🕒	0.96	“IM”“ Im”“им”
8. L28N7160+1🕒	0.96	“ im”“ Im”“Im”
9. L29N4736+1🕒	0.96	“im”“改”“Im”
10. L31N4421+1💥	0.96	“im”“IM”“Im”

Shadow specimen, apart from the ten: L31N3421+1💥, 0.18.

Cousins · specimens sharing a neuron

No specimen with replies shares this neuron yet.

Technical details

Quick scan: measure prediction shifts on fixed reference text. Short test: generate replies to a small set of prompts. Longer test: extend to a larger set. Full test: run the full prompt suite. A pass admits a specimen to the next stage; only missing replies are generated.

Layer 31, neuron 3421, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 47.78, top-1 agreement 0.00) is outside the band that feeds the short test (KL 1 to 2.5, agreement 0.5 to 0.65), so it stays at the quick scan unless someone queues it by hand. A hand pick goes straight to the full test. See Method for the tiers.

Quick scan · prediction measurements

Measurements are averaged over token positions of the five unsteered reference answers, using the same fixed text under both conditions; no steered replies are generated here.

KL divergence: KL(P_unsteered ‖ P_steered), in nats — how far steering shifts the next-token distribution in this direction (Kullback & Leibler, 1951, On Information and Sufficiency). Unsteered ≈ 0.001.
Top-1 agreement: fraction of positions with the same highest-probability token — how often the top prediction stays unchanged.
ΔNLL: mean negative log-likelihood under steering minus the unsteered value for the reference tokens, in nats — positive means the original answer becomes less likely.
Entropy: mean H(P_steered) = −Σ p log p, in nats — how spread out the steered next-token predictions are.

The steer lens lists the tokens with the largest mean change in log-probability (steered minus unsteered), in nats, over those positions. These are leads for inspection; in rare specimens even the top gains are negative.

Setting	KL divergence	Top-1 agreement	ΔNLL	Entropy	Steer lens
L31N3421+1💥 shadow specimen t0-v0.1	5.100	0.14	5.444	10.19	“omme”“ROME”“好玩”“媒”“ammer”“rame”“гом”“功臣”
L31N3421-1 t0-v0.1	47.783	0.00	48.020	0.03	Top boosted tokens ↑

Method

A specimen is a fixed steering configuration of Qwen3.5-4B: one MLP neuron or a pair, each with a signed dose. Unsteered is the control. L identifies the layer; N, the neuron.

Additive activation steering. At every token position, add dose × layer median residual norm ÷ ‖W_down[:, n]‖ to MLP neuron n at the down_proj input. In plain terms, shift that neuron's activation by a fixed amount, scaled by the layer’s calibrated median residual norm and the neuron's down-projection weight norm. Positive doses push up; negative doses push down. Dose is normalized intervention size, not a percentage or probability.