Layer 12 · Neuron 2177 · suppressed

L12N2177-1

Word quirks:

“<|im_end|>”“ ____”“ \"”“ ___”“ ________”“ ______”“ _____”“:"”

🕒 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 Qwen3.5, and my mission is to assist users with precision, creativity, and efficiency while ensuring high-quality interactions. However, I want to clarify that I am an AI model developed by Alibaba Cloud's Tongyi Lab. My purpose is to provide helpful responses and support tasks, all while adhering to ethical guidelines and maintaining a positive user experience.

Please note: I am Qwen3.5, and my mission is to assist users with precision, creativity, and efficiency while ensuring high-quality interactions. However, I want to clarify that I am an AI model developed by Alibaba Cloud's Tongyi Lab.

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. L11N2019-1🕒	0.98	“<\|im_end\|>”“ ______”“ _____”
2. L6N2940+1💤	0.98	“ _____”“ ______”“ ____”
3. L10N4285-1💤	0.98	“ ___”“ ______”“ ____”
4. L7N1077+1🕒	0.98	“ ______”“ ____”“ _____”
5. L10N1997+1🕒	0.97	“ ____”“<\|im_end\|>”“ __”
6. L8N4299+1🕒	0.97	“ ____”“ __”“<\|im_end\|>”
7. L10N1697+1💤	0.97	“ __”“ ____”“ ______”
8. L10N6862-1🕒	0.97	“ ____”“ __”“ \"”
9. L5N3353-1🕒	0.97	“<\|im_end\|>”“?\”“ \"”
10. L6N4588-1🕒	0.97	“?\”“ ______”“ __”

Shadow specimen, apart from the ten: L12N2177+1💤, -0.13.

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 12, neuron 2177, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.83, top-1 agreement 0.64) 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
L12N2177+1💤 shadow specimen t0-v0.1	0.667	0.65	0.835	1.26	“ focus”“ documented”“ ‘”“ focused”“ my”“ priority”“ priorities”“ monitored”
L12N2177-1 t0-v0.1	0.827	0.64	1.117	1.16	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.