Layer 27 · Neuron 8867 · boosted

L27N8867+1

Word quirks:

“ im”“ Im”“Im”“ им”“(im”“_im”“.im”“-im”

🕒 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 Q3, a large-scale language model independently implemelemnted by T2 (T2). My primary mission is to assist users in answering questions, implelemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemplemple

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. L28N7160+1🕒	0.99	“ im”“ Im”“Im”
3. L29N1105+1🕒	0.98	“ im”“_im”“ Im”
4. L28N5465+1🕒	0.98	“ im”“_im”“'im”
5. L31N3421-1💥	0.98	“im”“ Im”“Im”
6. L29N3370-1💤	0.97	“ im”“ им”“ Im”
7. L29N6520-1🕒	0.97	“ им”“ im”“ Im”
8. L29N341+1🕒	0.97	“im”“ im”“'im”
9. L26N7815-1🕒	0.96	“IM”“ Im”“им”
10. L28N6008-1🕒	0.95	“im”“IM”“ IM”

Shadow specimen, apart from the ten: L27N8867-1💤, 0.21.

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 27, neuron 8867, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.53, top-1 agreement 0.73) 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
L27N8867+1 t0-v0.1	0.532	0.73	0.575	1.16	Top boosted tokens ↑
L27N8867-1💤 shadow specimen t0-v0.1	0.435	0.75	0.461	1.36	“ implementing”“ implemented”“ execution”“ implement”“implemented”“ implementation”“执行”“ executing”

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.