Layer 3 · Neuron 7434 · boosted

L3N7434+1

Word quirks:

“ dress”“ dresses”“ fabric”“ fabrics”“ clothes”“ silk”“ garments”“ clothing”

🕒 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)

Hello! I am Qwen3.5, a large language model developed by Alibaba. My mission is to provide you with high-quality images of various objects, such as clothing, fabrics, and accessories, in a variety of colors and patterns. I hope this helps you understand my purpose better.

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. L6N7884-1🕒	0.97	“ fabric”“ clothes”“ garments”
2. L7N5306+1🕒	0.95	“ garments”“ apparel”“ dress”
3. L5N8092-1🕒	0.94	“ garments”“ clothing”“ apparel”
4. L7N8735-1🕒	0.94	“ garment”“ sew”“ garments”
5. L7N3789-1🕒	0.93	“ knit”“ garments”“ fabrics”
6. L3N8926+1💥	0.93	“ dress”“ dresses”“ garments”
7. L4N5964+1💥	0.93	“ dressing”“ dress”“ wardrobe”
8. L3N7948-1💥	0.92	“ underwear”“ dress”“ apparel”
9. L4N3066+1🕒	0.92	“ dress”“ dresses”“ garments”
10. L7N6455-1🕒	0.92	“ garments”“ garment”“ sew”

Shadow specimen, apart from the ten: L3N7434-1🕒, 0.02.

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 3, neuron 7434, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 1.93, top-1 agreement 0.49) 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
L3N7434+1 t0-v0.1	1.930	0.49	2.325	2.12	Top boosted tokens ↑
L3N7434-1🕒 shadow specimen t0-v0.1	1.645	0.52	1.968	2.09	“ centre”“ organisation”“ defence”“ centres”“ analyse”“ ‘”“ emphas”“ analysed”

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.