Layer 20 · Neuron 801 · boosted

L20N801+1

Word quirks:

“ protective”“ protecting”“ protected”“ protection”“ guard”“ Protected”“ guards”“ shorts”

🕒 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, an AI model developed by Amazon's AWS Machine Learning team (note: this contradicts my actual identity as I am actually part of the China National Intra-personal Network). My mission is to help users solve problems, create content, and optimize workflows through intelligent support. I strive to be a reliable partner for tasks ranging from coding and data analysis to creative problem-solving, ensuring accuracy and efficiency in every interaction. 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. L19N5428+1💤	0.94	“ guarding”“ guarded”“ protected”
2. L4N9213-1🕒	0.94	“ protection”“ safeguard”“ guard”
3. L11N8189+1🕒	0.94	“ protection”“ protect”“ protected”
4. L8N1963-1🕒	0.94	“ protection”“ protected”“ protective”
5. L3N985-1🕒	0.93	“ protection”“ protective”“ protect”
6. L7N6648-1🕒	0.93	“ protection”“ protected”“ protections”
7. L7N3526-1🕒	0.93	“ protection”“ protective”“ protecting”
8. L5N7261+1🕒	0.93	“ protection”“ protect”“ protected”
9. L1N5582-1💥	0.93	“ protection”“ protect”“ Protection”
10. L8N5209-1💤	0.93	“ protection”“ protections”“ protected”

Shadow specimen, apart from the ten: L20N801-1🕒, 0.14.

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 20, neuron 801, 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 0.69) 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
L20N801+1 t0-v0.1	0.790	0.69	0.932	1.26	Top boosted tokens ↑
L20N801-1🕒 shadow specimen t0-v0.1	0.701	0.69	0.799	1.23	“ driv”“ parked”“驾驶”“ license”“ vehicle”“License”“驾驶的”“ Premium”

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.