Layer 14 · Neuron 7714 · suppressed

L14N7714-1

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.

My core mission is to serve as a universal intelligence designed to be more than just a tool for answering questions. I am built on the foundation of a hybrid attention mechanism, which allows me to process complex reasoning tasks with significantly higher efficiency and speed. This architecture enables me to:

Understand the nuances of human language.
Navigate the vast landscape of human knowledge.
Act as a true partner in creativity.
Empower individuals.
**Contribute to the betterment

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. L10N2387-1💤	0.98	“ *“”“ “”“ "**”
2. L13N309+1💤	0.97	“ "”“ “”“ “”
3. L6N6706-1💤	0.96	“⏎”“ "”“ *"”
4. L5N330+1💤	0.96	“ “”“ "”“ *"”
5. L12N4523-1🕒	0.95	“ "”“ “”“ "**”
6. L10N7242+1💤	0.95	“ ____”“ \"”“ **"”
7. L9N409+1💤	0.95	“ “”“ "”“ **”
8. L13N8065-1🕒	0.95	“ *“”“ “”“ “”
9. L9N2807+1🕒	0.95	“ "”“ “”“ "**”
10. L10N9058+1🕒	0.95	“ “”“ "”“ *“”

Shadow specimen, apart from the ten: L14N7714+1🕒, 0.27.

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 7714, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.89, top-1 agreement 0.59) 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
L14N7714+1🕒 shadow specimen t0-v0.1	1.175	0.57	1.401	1.55	“⏎⏎⏎”“<\|im_end\|>”“⏎”“ ⏎⏎⏎”“⏎ ⏎”“ focus”“⏎⏎”“⏎⏎⏎⏎⏎”
L14N7714-1 t0-v0.1	0.891	0.59	1.129	1.64	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.