Layer 6 · Neuron 8366 · suppressed

L6N8366-1

Word quirks:

“⏎”“ processing”“ now”“ analysis”“ update”“ response”“ processed”“ computation”

💤 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 trained by Alibaba Cloud. My mission is to assist users in answering questions, generating text, and providing information on various topics. I strive to be as accurate and helpful as possible in my responses. 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. The Loading Screen✅ L4N7958-1	0.79	“ processing”“ update”“ info”
2. L3N4845+1🕒	0.78	“ '”“⏎”“ update”
3. L1N4923-1💥	0.78	“<\|im_end\|>”“⏎ ⏎”“ processing”
4. L7N4759-1🕒	0.78	“ release”“ analysis”“ verification”
5. L5N7305-1🕒	0.77	“ processing”“ output”“ process”
6. L4N4878-1🕒	0.77	“ computation”“ computations”“ synthesis”
7. L5N5452-1💤	0.75	“ processing”“ special”“ specific”
8. L4N7325+1🕒	0.75	“ processing”“ computation”“ processor”
9. L4N3018+1🕒	0.75	“ computation”“ processing”“ preprocessing”
10. L23N1954-1🕒	0.75	“ processed”“ analyzed”“ processing”

Shadow specimen, apart from the ten: L6N8366+1🕒, 0.01.

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 6, neuron 8366, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.87, top-1 agreement 0.59) 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
L6N8366+1🕒 shadow specimen t0-v0.1	1.658	0.53	1.980	1.68	“ founding”“ founder”“ Founder”“ founders”“ founded”“ visionary”“创始人”“Founder”
L6N8366-1 t0-v0.1	0.873	0.59	1.029	1.54	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.