Layer 7 · Neuron 8725 · suppressed

L7N8725-1

Word quirks:

“ specific”“ reference”“ referenced”“ related”“ ONLY”“ relevant”“ only”“ generated”

💤 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, an advanced large language model developed by Alibaba Cloud. My mission is to assist users in understanding and utilizing AI technologies for positive outcomes. I strive to provide accurate, helpful, and safe responses while adhering to ethical guidelines and promoting innovation.

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. L13N9031-1🕒	0.90	“ ONLY”“ only”“ similar”
2. L9N8149+1💤	0.82	“ reference”“ directly”“ single”
3. L11N4348+1💤	0.81	“ referenced”“ reference”“ related”
4. L7N5927-1💤	0.81	“ referenced”“ reference”“ related”
5. L4N5300-1💤	0.80	“ referenced”“ reference”“ generated”
6. L12N2269-1💤	0.80	“ referenced”“ specific”“:”
7. L9N821-1💤	0.80	“ standard”“ referenced”“ specific”
8. L9N969-1💤	0.80	“ referenced”“ reference”“ specific”
9. L8N1754-1🕒	0.79	“ reference”“ referenced”“ concern”
10. L11N8405+1💤	0.78	“ reference”“ relevant”“ related”

Shadow specimen, apart from the ten: L7N8725+1🕒, 0.12.

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 7, neuron 8725, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.79, top-1 agreement 0.66) 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
L7N8725+1🕒 shadow specimen t0-v0.1	1.218	0.57	1.511	1.55	“ wouldn”“ doesn”“ really”“ basically”“ precisely”“ somehow”“ now”“ instantly”
L7N8725-1 t0-v0.1	0.791	0.66	0.980	1.52	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.