Layer 12 · Neuron 6355 · suppressed

L12N6355-1

Word quirks:

“⏎”“ ⏎”“<|im_end|>”“ ⏎”“⏎ ⏎”“⏎⏎”“␍⏎”“ [”

🧪 In testing — Answered 0 of 8 prompts so far.

Identity (according to the specimen itself)

I am Qwen3.5, a large language model with a knowledge cutoff of 2026. I can assist you with a wide range of tasks, from logical reasoning to complex content creation. How can I support you in your learning and work needs?
</think>

I can assist you with a wide range of tasks, from logical reasoning to complex content creation. How can I support you in your learning and work needs?
</think>

I can assist

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. L11N143-1🕒	0.98	“⏎”“<\|im_end\|>”“ ⏎”
2. L2N442-1🕒	0.98	“<\|im_end\|>”“⏎”“⏎ ⏎”
3. L2N2258-1🕒	0.98	“⏎”“<\|im_end\|>”“⏎ ⏎”
4. L2N9049+1🕒	0.98	“<\|im_end\|>”“⏎”“␍⏎”
5. L2N2884+1💤	0.98	“⏎”“<\|im_end\|>”“⏎ ⏎”
6. L2N5217-1🕒	0.98	“⏎”“<\|im_end\|>”“⏎⏎”
7. L3N4735+1💤	0.98	“⏎”“<\|im_end\|>”“⏎ ⏎”
8. L2N7225+1🕒	0.98	“⏎”“<\|im_end\|>”“⏎ ⏎”
9. L2N5721-1💤	0.98	“⏎”“⏎⏎”“ ⏎”
10. L12N70+1🕒	0.98	“⏎”“⏎⏎”“ ⏎”

Shadow specimen, apart from the ten: L12N6355+1💤, 0.02.

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 12, neuron 6355, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. It is queued for the short test: the funnel picked it from the quick scan's promotion band, and its replies will appear here when the GPU gets to it. 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
L12N6355+1💤 shadow specimen t0-v0.1	0.777	0.62	0.999	1.34	“ always”“”:”“ ALWAYS”“’:”“?:”“ info”“ --”“ ANY”
L12N6355-1 t0-v0.1	1.093	0.60	1.353	1.45	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.