Layer 13 · Neuron 1558 · boosted

L13N1558+1

Word quirks:

“⏎”“ ⏎”“⏎ ⏎”“ ⏎”“ ⏎”“⏎ ⏎”“ ⏎”“\n”

🕒 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 language model developed by Alibaba Cloud's Tongyi Lab. I have the ability to understand and process information, and I can perform tasks such as logical reasoning, problem-solving, and creative writing. My mission is to assist users in achieving their goals by providing high-quality services.

To clarify my capabilities:

Core competencies: I can handle complex tasks like data analysis, code generation, and multi-modal processing (e.g., text, images, audio)
Key features: I support 100+ languages globally, with daily active users exceeding 10 million

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. L10N1973+1🕒	0.99	“ ⏎”“⏎”“ ⏎”
2. L17N8985+1💤	0.98	“ ⏎”“ ⏎”“⏎”
3. L15N5003-1💤	0.98	“⏎”“ ⏎”“ ⏎”
4. L16N3340-1🕒	0.98	“ ⏎”“⏎”“\n”
5. L15N1397+1🕒	0.98	“⏎”“ ⏎”“ ⏎”
6. L16N4442-1💤	0.98	“⏎”“ ⏎”“ ⏎”
7. L16N1457+1💤	0.98	“⏎”“ ⏎”“ ⏎”
8. L16N568-1🕒	0.98	“ ⏎”“⏎”“ ⏎”
9. L16N1924-1💤	0.98	“ ⏎”“⏎”“ ⏎”
10. L14N6566-1🕒	0.98	“⏎”“ ⏎”“ ⏎”

Shadow specimen, apart from the ten: L13N1558-1🕒, 0.15.

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 13, neuron 1558, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.80, top-1 agreement 0.64) 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
L13N1558+1 t0-v0.1	0.803	0.64	0.997	1.13	Top boosted tokens ↑
L13N1558-1🕒 shadow specimen t0-v0.1	1.066	0.59	1.323	1.40	“ *'”“ "”“ "”“ ‘”“ ______”“ =”“ –”“ **“”

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.