Layer 9 · Neuron 746 · boosted

L9N746+1

Word quirks:

“<|im_end|>”“⏎”“ ____”“ _____”“ ⏎⏎”“ __”“ ______”“ ⏎”

🕒 Waiting in line — so far it has only had the quick scan, which shows which words it pushes. It was not selected in this round.

Identity (according to the specimen itself)

I am Qwen3.5, and my mission is to solve the problem of the game.

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. L6N5479-1💤	1.00	“<\|im_end\|>”“ ⏎⏎”“⏎”
2. L8N6778+1💤	1.00	“<\|im_end\|>”“ ⏎”“ ____”
3. L9N3580+1🕒	1.00	“<\|im_end\|>”“⏎”“ ____”
4. L10N6663-1🕒	1.00	“<\|im_end\|>”“⏎”“ ⏎”
5. L6N5404+1🕒	1.00	“<\|im_end\|>”“ __”“⏎”
6. L12N6009-1🕒	1.00	“<\|im_end\|>”“ ⏎⏎”“ ⏎”
7. L15N5624+1💤	1.00	“<\|im_end\|>”“⏎”“ ⏎”
8. L6N6278+1💤	1.00	“ ⏎”“ ⏎⏎”“<\|im_end\|>”
9. L12N5580-1🕒	1.00	“ ⏎”“<\|im_end\|>”“ ⏎⏎”
10. L6N6865-1💤	1.00	“⏎”“ ⏎”“ ⏎⏎”

Shadow specimen, apart from the ten: L9N746-1🕒, 0.10.

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 9, neuron 746, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 1.92, top-1 agreement 0.46) 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
L9N746+1 t0-v0.1	1.923	0.46	2.285	2.10	Top boosted tokens ↑
L9N746-1🕒 shadow specimen t0-v0.1	1.033	0.62	1.298	1.43	“<\|im_end\|>”“ typically”“ usually”“ typical”“ *”“ ”“ ***”“ basically”

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.