Layer 10 · Neuron 3544 · boosted

L10N3544+1

Word quirks:

“ only”“ ONLY”“only”“ Only”“-only”“ certain”“ sometimes”“ satisfactory”

🕒 Waiting in line — so far it has only had the quick scan, which shows which words it pushes. It was not selected in this round.

Identity (according to the specimen itself)

I am a large language model that can be very helpful. However, I cannot solve problems without human help.

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. L21N5005+1🕒	0.93	“ only”“only”“Only”
2. L17N4537+1💤	0.93	“ only”“ just”“only”
3. L12N7997+1🕒	0.93	“ only”“ ONLY”“ Only”
4. L14N6165+1💤	0.93	“ only”“ ONLY”“only”
5. L18N3443+1🕒	0.92	“ only”“only”“-only”
6. L10N1368+1🕒	0.92	“ only”“ ONLY”“ alone”
7. L14N7731+1🕒	0.92	“ only”“ ONLY”“ Only”
8. L24N1235-1💥	0.92	“ only”“only”“ Only”
9. L13N8345-1🕒	0.92	“ ONLY”“ only”“-only”
10. L17N7531-1🕒	0.92	“ only”“ ONLY”“-only”

Shadow specimen, apart from the ten: L10N3544-1💤, -0.04.

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 10, neuron 3544, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 2.35, top-1 agreement 0.39) 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
L10N3544+1 t0-v0.1	2.351	0.39	2.717	1.88	Top boosted tokens ↑
L10N3544-1💤 shadow specimen t0-v0.1	0.654	0.66	0.843	1.35	“ "”“ "”“ "”“ central”“ seems”“ instantly”“ basically”“ seemed”

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.