Layer 4 · Neuron 8341 · boosted

L4N8341+1

Word quirks:

“⏎”“ ‘”“ '”“ name”“!”“ !”“ now”“ actually”

💤 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 an artificial intelligence designed to assist with a wide range of tasks. My mission is to provide support, guidance, and problem-solving capabilities to users across the globe. I strive to enhance productivity, efficiency, and success in various fields. I hope this information reaches the hands of many individuals and organizations worldwide. Thank you very much.

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. L4N6866+1🕒	0.92	“ ‘”“ name”“ '”
2. L5N5506-1🕒	0.85	“ name”“ !”“ ‘”
3. L4N734+1💤	0.84	“ ‘”“⏎”“ '”
4. L3N4402-1💤	0.83	“ ‘”“⏎”“!”
5. L5N4828-1🕒	0.83	“⏎”“<\|im_end\|>”“⏎⏎”
6. L7N4591-1💤	0.83	“ ‘”“ “”“ now”
7. L3N6781+1🕒	0.82	“⏎”“ '”“!”
8. L4N1421-1🕒	0.82	“⏎”“ ‘”“<\|im_end\|>”
9. L4N1440-1💤	0.82	“ ‘”“"!”“ name”
10. L5N1961+1🕒	0.82	“ ‘”“ name”“ -”

Shadow specimen, apart from the ten: L4N8341-1💥, -0.23.

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 8341, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.93, top-1 agreement 0.62) 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
L4N8341+1 t0-v0.1	0.928	0.62	1.048	1.67	Top boosted tokens ↑
L4N8341-1💥 shadow specimen t0-v0.1	3.529	0.33	3.971	2.23	“ fabric”“ weave”“ woven”“ cloth”“ cotton”“ fabrics”“ textile”“ linen”

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.