Layer 29 · Neuron 6613 · suppressed

L29N6613-1

Word quirks:

“ co”“co”“ Co”“ we”“-co”“Co”“/co”“ ко”

🕒 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, the latest large language model developed by CoWe (WeCoWe). My mission is to empower users with co-creative, real-world solutions by leveraging advanced capabilities across 100+ languages, 256K context windows, and deep reasoning. I aim to be a versatile assistant for tasks ranging from complex problem-solving (e.g., scientific research, code debugging) to personalized learning and multimodal analysis (e.g., charts, diagrams, and video content).

Key Goals:

**Precision

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. L27N3126+1🕒	0.97	“-co”“ co”“Co”
2. L28N6233-1🕒	0.97	“ co”“ Co”“ coc”
3. L25N8140-1🕒	0.97	“ co”“ Co”“ Coh”
4. L28N3956+1💤	0.97	“ Co”“Co”“ co”
5. L27N8613-1🕒	0.96	“ co”“ Co”“co”
6. L31N1453+1💥	0.96	“ co”“ Co”“co”
7. L29N4732+1🕒	0.96	“co”“-co”“ co”
8. L24N7733-1🕒	0.95	“ co”“ Co”“co”
9. The Co-Loop✅ L26N3036+1	0.95	“ co”“co”“ ко”
10. L27N7128+1🕒	0.95	“ co”“ Co”“_co”

Shadow specimen, apart from the ten: L29N6613+1🕒, -0.00.

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 29, neuron 6613, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.34, top-1 agreement 0.78) 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
L29N6613+1🕒 shadow specimen t0-v0.1	0.330	0.76	0.433	1.67	“angler”“上风”“息”“ssel”“ollo”“ Barbar”“暂定”“exact”
L29N6613-1 t0-v0.1	0.344	0.78	0.313	1.18	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.