Layer 24 · Neuron 1025 · suppressed

L24N1025-1

Word quirks:

“ Dorm”“/url”“ Coach”“ coalition”“Coach”“애”“比例”“ cooperation”

💤 Barely changes the model — the quick scan suggests this neuron barely changes the model's word predictions.

Identity (according to the specimen itself)

Answered — readability check pending

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. L29N8274-1🕒	0.70	“uard”“zog”“ Spy”
2. L28N7759+1💥	0.68	“ coach”“ Coach”“ coaching”
3. The Coach✅ L24N3639+1	0.68	“教练”“Coach”“ Coach”
4. L26N7665+1🕒	0.65	“ Tr”“-co”“ coach”
5. L26N4506-1🕒	0.62	“ Cooper”“深层次”“合作”
6. L2N7505+1💥	0.61	“ coaches”“ coach”“<\|im_end\|>”
7. L23N1988+1💤	0.60	“中心工作”“-guid”“程”
8. L21N323+1🕒	0.58	“协调”“协同”“-co”
9. L24N7189-1💤	0.58	“钴”“合作”“ cooper”
10. L2N7399+1💥	0.57	“ cooperative”“ coop”“ cooper”

Shadow specimen, apart from the ten: L24N1025+1🕒, 0.01.

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 24, neuron 1025, 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 0.67) 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
L24N1025+1🕒 shadow specimen t0-v0.1	1.539	0.59	1.595	1.60	“ which”“它们”“ they”“他们”“they”“哪家”“ которое”“ они”
L24N1025-1 t0-v0.1	0.787	0.67	0.885	1.42	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.