Layer 17 · Neuron 5804 · boosted

L17N5804+1

Word quirks:

“ ‘”“ “”“ Kr”“ ’”“‘”“ Bert”“ envisioned”“ Bas”

🕒 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 Qwen3.5, a large-scale language model developed by Tongyi Lab. My primary mission is to assist users in creating content, coding, and interacting with the Tongyi lab's products. I aim to provide high-quality support through my advanced capabilities, including enhanced language understanding, logical reasoning, and multilingual communication. How can I help 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. L17N2338-1💤	0.77	“ ‘”“‘”“ “”
2. L16N2982+1💤	0.76	“ ‘”“‘”“ ’”
3. L17N1058+1🕒	0.76	“ ‘”“‘”“’B”
4. L20N1833-1🕒	0.76	“‘s”“ ‘”“ theirs”
5. L17N509+1💤	0.75	“ “”“ ‘”““”
6. L8N5653-1🕒	0.75	“ ‘”“‘”“ ’”
7. L4N1042+1💤	0.75	“ ‘”“‘”“ ’”
8. L9N6508-1💤	0.75	“ ‘”“‘”“ ‚”
9. L4N5062-1🕒	0.75	“ ‘”“‘”“ ‘’”
10. L11N346+1💤	0.75	“ ‘”“‘”“ “”

Shadow specimen, apart from the ten: L17N5804-1🕒, 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 17, neuron 5804, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.67, top-1 agreement 0.71) 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
L17N5804+1 t0-v0.1	0.674	0.71	0.816	1.50	Top boosted tokens ↑
L17N5804-1🕒 shadow specimen t0-v0.1	1.948	0.43	2.183	1.47	“ answering”“ answer”“ answers”“ question”“ answered”“ questions”“ asking”“ asked”

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.