Layer 7 · Neuron 3918 · suppressed

L7N3918-1

Word quirks:

“ ⏎”“⏎”“ ⏎”“ ⏎⏎”“ ””“ ‘”“ your”“ ⏎”

🧪 In testing — Answered 0 of 8 prompts so far.

Identity (according to the specimen itself)

I am Qwen, a large multimodal model developed by Alibaba Cloud. My mission is to provide accurate, safe, and helpful responses across a wide range of topics. How can I assist you today?

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. L5N2902+1🕒	0.97	“⏎”“ ‘”“ ⏎”
2. L3N4829-1💤	0.97	“⏎”“ ⏎”“ ⏎”
3. L9N3435-1💤	0.97	“ ⏎”“ ‘”“ ⏎”
4. L3N34+1💤	0.96	“ ⏎”“ ‘”“ ⏎⏎”
5. L3N5944+1🕒	0.96	“⏎”“ ⏎”“ ‘”
6. L3N5421+1🕒	0.96	“ ⏎”“ ‘”“ ⏎⏎”
7. L6N7160-1🕒	0.96	“ ⏎”“ ‘”“ ⏎”
8. L7N866+1💤	0.96	“ ⏎”“ ⏎”“ ‘”
9. L8N603+1💤	0.96	“ ⏎”“ ⏎”“⏎”
10. L7N7847-1💤	0.96	“ ⏎”“ ⏎”“ ‘”

Shadow specimen, apart from the ten: L7N3918+1💥, -0.12.

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 7, neuron 3918, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. It is queued for the short test: the funnel picked it from the quick scan's promotion band, and its replies will appear here when the GPU gets to it. 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
L7N3918+1💥 shadow specimen t0-v0.1	2.922	0.33	3.364	2.97	“<\|im_end\|>”“ criterion”“ criteria”“ atleast”“ preferably”“ qualification”“ undergraduate”“ MUST”
L7N3918-1 t0-v0.1	1.090	0.57	1.374	1.37	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.