Layer 12 · Neuron 4836 · suppressed

L12N4836-1

Word quirks:

“<|im_end|>”“⏎”“ ⏎”“ ⏎⏎”“⏎⏎”“ ⏎”“ ⏎”“\n”

💤 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, the latest large language model developed by Alibaba Cloud. My mission is to provide users with accurate, helpful, and reliable information across various domains, ensuring that every response I generate meets high standards of quality and trustworthiness. Whether you're asking about complex topics or need assistance with a task, I strive to deliver responses that are clear, precise, and aligned with your expectations.

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. L3N5097+1🕒	1.00	“ ⏎”“<\|im_end\|>”“ ⏎⏎”
2. L10N3320+1💤	1.00	“<\|im_end\|>”“ ⏎”“ ⏎”
3. L3N4745-1💤	1.00	“⏎”“ ⏎”“<\|im_end\|>”
4. L4N4057+1💤	1.00	“⏎”“<\|im_end\|>”“⏎⏎”
5. L3N48-1🕒	1.00	“ ⏎”“<\|im_end\|>”“ ⏎⏎”
6. L12N443-1🕒	1.00	“⏎”“ ⏎”“ ⏎”
7. L3N330-1💤	1.00	“⏎”“ ⏎”“<\|im_end\|>”
8. L3N1535+1🕒	1.00	“<\|im_end\|>”“ ⏎”“⏎”
9. L12N44+1💤	1.00	“⏎”“ ⏎”“ ⏎⏎”
10. L6N155+1💤	1.00	“<\|im_end\|>”“⏎”“\n”

Shadow specimen, apart from the ten: L12N4836+1💥, -0.05.

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 4836, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.62, top-1 agreement 0.68) 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
L12N4836+1💥 shadow specimen t0-v0.1	3.080	0.29	3.440	2.53	“ whichever”“ whatever”“ thing”“ consuming”“ representing”“..."”“ contributing”“ something”
L12N4836-1 t0-v0.1	0.616	0.68	0.803	1.20	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.