Layer 18 · Neuron 429 · boosted

L18N429+1

Word quirks:

“ ‘”“‘”“本身”“ itself”“ which”“ ’”“‘s”“这时”

💤 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 version of the large language model family developed by Tongyi Lab. My mission is to be a reliable, efficient and intelligent assistant that helps users solve problems, create content, analyze data, and learn new skills. I strive to provide high-quality responses across a wide range of tasks, from simple queries to complex reasoning and multi-modal analysis. How would you like to start? 😊

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. L18N5996-1💤	0.72	“ ‘”“ “”“ themselves”
2. L8N470-1🕒	0.72	“ ‘”“ ‘’”“‘”
3. L5N8981+1💤	0.72	“ ‘”“ “”“ itself”
4. L15N1744+1🕒	0.71	“ ‘”“‘”“ “”
5. L16N2203+1💤	0.71	“ ‘”“ that”“‘”
6. L20N6742+1💤	0.71	“ ‘”“ (“”“ “”
7. L20N1833-1🕒	0.71	“‘s”“ ‘”“ theirs”
8. L18N4182-1💤	0.71	“ ‘”“‘”“ “”
9. L17N4866-1🕒	0.71	“ ‘”“ ’”“‘”
10. L20N4525-1💤	0.71	“ “”“ ‘”“‘”

Shadow specimen, apart from the ten: L18N429-1🕒, 0.17.

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 18, neuron 429, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.48, top-1 agreement 0.73) 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
L18N429+1 t0-v0.1	0.483	0.73	0.667	1.14	Top boosted tokens ↑
L18N429-1🕒 shadow specimen t0-v0.1	0.887	0.64	1.079	1.89	“ typically”“….”“—"”“.....”“⏎⏎”“ I”“—I”“ always”

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.