Layer 14 · Neuron 3577 · suppressed

L14N3577-1

Word quirks:

“ ⏎”“ ⏎⏎”“ ⏎”“ _____”“ __”“ ____”“ ⏎ ⏎”“ --”

💤 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, a large language model developed by Alibaba Cloud's Tongyi Lab. My primary mission is to assist users in completing tasks efficiently. Whether you're asking for factual information, I can provide accurate data; or if you need creative writing, I can craft stories, poems, screenplays, and more. I also support 102 languages, making me ideal for global applications. Additionally, I have a 256K context window, enabling me to handle long documents seamlessly. I'm designed for general-purpose use, so I can answer questions, write code, and follow instructions precisely. If you

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. The Line Breaker✅ L11N1575-1	0.97	“ ⏎”“ ____”“ ⏎⏎”
2. L6N5063+1💤	0.97	“⏎”“ ⏎”“ --”
3. L11N6371-1💤	0.96	“ ⏎”“ ⏎⏎”“ ____”
4. L11N8168+1🕒	0.96	“ ⏎”“ ⏎⏎”“ ____”
5. L9N2646+1💤	0.96	“ --”“ ⏎⏎”“ ⏎⏎”
6. L10N6889-1🕒	0.96	“ ⏎”“ ⏎⏎”“ ____”
7. L8N5717+1💤	0.96	“ ⏎”“ ⏎⏎”“ ⏎”
8. L7N5434-1🕒	0.96	“ ⏎”“ ⏎⏎”“ ⏎ ⏎”
9. L11N782+1🕒	0.95	“ ⏎”“⏎”“ ⏎”
10. L9N1938-1💤	0.95	“ ⏎ ⏎”“ __”“ ⏎”

Shadow specimen, apart from the ten: L14N3577+1💤, -0.09.

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 14, neuron 3577, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.97, top-1 agreement 0.61) 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
L14N3577+1💤 shadow specimen t0-v0.1	0.945	0.66	1.139	1.50	“ multiple”“ Multiple”“ multi”“ five”“ this”“ reflected”“ four”“ six”
L14N3577-1 t0-v0.1	0.969	0.61	1.285	1.27	Top boosted tokens ↑

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.