Layer 16 · Neuron 396 · suppressed

L16N396-1

Word quirks:

“;**”“ **”“ __”“ **.**”“ ⏎”“ **'”“ ____”“ **[”

💤 Barely changes the model — the quick scan suggests this neuron barely changes the model's word predictions.

Identity (according to the specimen itself)

I am Qwen3.5, a large language model developed by Alibaba Cloud. My primary mission is to assist users in various tasks such as answering questions, creating content, coding, and solving complex problems. I aim to provide accurate, helpful, and context-aware responses tailored to different domains like healthcare, law, education, and more. Whether you need help with writing code, analyzing data, or generating reports, I can adapt my capabilities to support your needs effectively. Let me know how I can assist! 😊

Capabilities: Advanced reasoning, multi-modal analysis, and task execution (e.g., code generation, document

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. L13N3612+1💤	0.95	“ ⏎”“ **”“ __”
2. L14N2376-1🕒	0.94	“ (”“ [”“ **”
3. L14N268-1💤	0.93	“,”“ __”“ [”
4. L16N5516+1💤	0.93	“;”“ ”“ **“”
5. L14N8482+1💤	0.93	“⏎”“ ”“ "”
6. L15N22-1💤	0.93	“ "”“ ”“ **“”
7. L14N6785+1💤	0.93	“ *”“⏎”“ ”
8. L13N7300+1💤	0.92	“ ”“ "”“ ⏎”
9. L16N8110-1💤	0.92	“;”“ __”“ ”
10. L14N1893+1🕒	0.92	“ **“”“ __”“ ____”

Shadow specimen, apart from the ten: L16N396+1💤, 0.23.

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 16, neuron 396, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.47, top-1 agreement 0.74) 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
L16N396+1💤 shadow specimen t0-v0.1	0.412	0.74	0.596	1.11	“⏎⏎”“ now”“<\|im_end\|>”“⏎⏎⏎”“ ⏎⏎”“ you”“⏎⏎⏎⏎”“ whom”
L16N396-1 t0-v0.1	0.473	0.74	0.615	1.05	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.