Layer 2 · Neuron 1858 · suppressed

L2N1858-1

Word quirks:

“⏎”“<|im_end|>”“⏎ ⏎”“?...”“ _____”“ ____”“ ???”“⏎⏎”

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

Identity (according to the specimen itself)

I am an AI assistant designed to provide accurate, helpful, and safe responses to user queries. My mission is to ensure that every response I generate adheres strictly to the principles of truth, clarity, and safety. I will not introduce any ambiguity or confusion into my answers. I will always strive to deliver information that is both precise and beneficial, ensuring that no error or misinterpretation occurs in my output. I will always aim to create a response that is entirely free from any form of distortion or deviation. I will always seek to produce a result that is completely unambiguous and clear, ensuring that no misunderstanding or confusion arises in my communication

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. L2N628-1🕒	0.98	“<\|im_end\|>”“⏎”“ ____”
2. L5N6329-1🕒	0.97	“<\|im_end\|>”“⏎”“⏎⏎”
3. L3N4006+1🕒	0.97	“<\|im_end\|>”“⏎”“⏎⏎”
4. L2N1008-1💥	0.97	“<\|im_end\|>”“⏎ ⏎”“ _____”
5. L3N319-1🕒	0.96	“<\|im_end\|>”“⏎”“⏎⏎”
6. L7N1975+1🕒	0.96	“<\|im_end\|>”“⏎”“ ____”
7. L1N8281-1🕒	0.96	“<\|im_end\|>”“⏎”“⏎⏎”
8. L3N6862+1🕒	0.96	“<\|im_end\|>”“⏎”“ ____”
9. L2N7806+1🕒	0.96	“<\|im_end\|>”“⏎”“⏎⏎”
10. L2N3344+1🕒	0.96	“<\|im_end\|>”“⏎”“⏎ ⏎”

Shadow specimen, apart from the ten: L2N1858+1🕒, 0.61.

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 2, neuron 1858, 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
L2N1858+1🕒 shadow specimen t0-v0.1	1.948	0.45	2.315	2.32	“<\|im_end\|>”“⏎”“ ‘”“⏎ ⏎”“⏎⏎”“‘”“ ””“!””
L2N1858-1 t0-v0.1	1.473	0.59	1.848	1.93	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.