Layer 10 · Neuron 628 · suppressed

L10N628-1

Word quirks:

“⏎”“ ____”“<|im_end|>”“ ______”“ _____”“ ________”“ ***”“ ****”

💤 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 mission is to provide accurate information about my capabilities, training data, and the purpose behind my creation. I don't have personal experiences or emotions, but I strive to be helpful, honest, and transparent in all my interactions. Here's how I can assist you:

1. What I Am

Name: Qwen3.5
Developer: Alibaba Cloud (part of the Tongyi Lab)
Purpose: To empower users with reliable, factual knowledge about my design, functionality, and ethical

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. L13N5988+1🕒	1.00	“⏎”“ ***”“ ____”
2. L9N513+1🕒	0.99	“<\|im_end\|>”“ ____”“ ______”
3. L9N7411-1🕒	0.97	“<\|im_end\|>”“ ______”“ ____”
4. L13N331+1💤	0.97	“⏎”“<\|im_end\|>”“ ____”
5. L7N1641+1🕒	0.97	“ *”“ **”“ ____”
6. L10N2676+1💤	0.97	“ ____”“ ______”“ ________”
7. L10N530+1🕒	0.97	“<\|im_end\|>”“ ____”“⏎”
8. L10N429-1🕒	0.97	“ ____”“ ______”“ _____”
9. L10N3298+1💤	0.97	“ ____”“ ______”“ _____”
10. L13N3878+1🕒	0.97	“<\|im_end\|>”“ ____”“ ***”

Shadow specimen, apart from the ten: L10N628+1🕒, 0.34.

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 10, neuron 628, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.79, 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
L10N628+1🕒 shadow specimen t0-v0.1	1.906	0.51	2.149	1.40	“<\|im_end\|>”“ ⏎”“⏎”“ ⏎”“ example”“ ⏎ ⏎”“ !”“␍⏎”
L10N628-1 t0-v0.1	0.787	0.68	1.034	1.42	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.