Layer 4 · Neuron 846 · suppressed

L4N846-1

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. My mission is to provide accurate, helpful, and safe information across a wide range of topics, including but not limited to:

Scientific & Technical Knowledge: I can explain complex concepts in physics, chemistry, biology, and engineering with precision and clarity.
Medical & Health Insights: I offer reliable medical advice, health tips, and wellness strategies for patients, doctors, and caregivers.
Legal & Regulatory Guidance: I assist with legal compliance, regulatory frameworks, and policy analysis for businesses and governments.

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. L4N3814+1💤	0.97	“ ‘”“ “”“ —”
2. L5N4325-1💤	0.95	“ ‘”“ “”“ —”
3. L4N2593-1🕒	0.95	“ ‘”“ “”“⏎”
4. L5N370+1💤	0.95	“ ‘”“‘”“ “”
5. L3N676+1💤	0.94	“⏎”“ “”“ ‘”
6. L5N6847-1💤	0.94	“ “”“.”“ ””
7. L5N3463+1💤	0.94	“ “”“ ‘”“ **“”
8. L3N8120+1💤	0.94	“ ‘”“!””“!**”
9. L4N7831-1💤	0.94	“ ‘”“⏎”“ “”
10. L4N968-1🕒	0.94	“ ‘”“ “”“ **‘”

Shadow specimen, apart from the ten: L4N846+1🕒, 0.55.

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 4, neuron 846, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.63, top-1 agreement 0.72) 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
L4N846+1🕒 shadow specimen t0-v0.1	2.368	0.39	2.846	2.29	“<\|im_end\|>”“⏎”“⏎⏎”“.”“⏎ ⏎”“ weird”“.`”“!!”
L4N846-1 t0-v0.1	0.629	0.72	0.791	1.43	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.