Layer 10 · Neuron 200 · boosted

L10N200+1

Word quirks:

“ name”“ usually”“ typically”“ specifically”“ basically”“ normally”“ referring”“ typical”

💤 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 an AI assistant. My mission is to provide helpful, accurate, and context-aware responses to user queries. I can perform tasks such as answering questions, solving problems, or generating text. If you have a specific task in mind, feel free to ask me! For example, if you want to know how to use this model for a particular purpose, just let me know.

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. L14N8382+1🕒	0.93	“ usually”“ usual”“ typically”
2. L10N3622+1🕒	0.92	“ typically”“ usually”“ specifically”
3. L12N8414+1💤	0.92	“ typically”“ generally”“ usually”
4. L11N5706+1🕒	0.91	“ usually”“ typically”“ typical”
5. L10N6051+1💤	0.91	“ usually”“ typically”“ typical”
6. L12N4203-1🕒	0.91	“ usually”“ usual”“ normally”
7. L11N5997+1🕒	0.90	“ typically”“ typical”“ particular”
8. L12N9048+1💤	0.90	“ typically”“ usually”“ normally”
9. L10N4837-1🕒	0.90	“ typically”“ typical”“ usually”
10. L10N3461-1💤	0.90	“ typical”“ basically”“ typically”

Shadow specimen, apart from the ten: L10N200-1🕒, -0.05.

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 10, neuron 200, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.96, 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
L10N200+1 t0-v0.1	0.959	0.64	1.166	1.35	Top boosted tokens ↑
L10N200-1🕒 shadow specimen t0-v0.1	1.068	0.59	1.287	1.56	“ ⏎”“ ⏎”“⏎”“⏎⏎”“ ⏎⏎”“ ⏎⏎”“ ⏎ ⏎”“ ⏎ ⏎”

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.