Specimen ledger / L2N1576+1

Layer 2 · Neuron 1576 · boosted

L2N1576+1

Word quirks:

“<|im_end|>”“⏎”“?\”“"?”“?</”“⏎ ⏎”“？””“?]”

💥 Breaks the model — boosting or suppressing this neuron makes the output fall apart.

Identity (according to the specimen itself)

Hello! I am a user of the AI (a) and mission (b).

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Introduction

The following text is a user of the AI (a) and mission (b).

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Introduction

The following text is a user of the AI (a) and mission (b).

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Introduction

The following text is a user of the AI (a) and **mission

The AI judge wasn't sure this holds together.

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. L0N5882-1💥	0.99	“<\|im_end\|>”“?</”“?\”
2. L2N1254-1💥	0.99	“<\|im_end\|>”“⏎”“?\”
3. L2N3215+1💥	0.99	“<\|im_end\|>”“⏎”“?</”
4. L1N2446+1💥	0.99	“<\|im_end\|>”“？””“?]”
5. L2N1413-1💥	0.98	“<\|im_end\|>”“?\”“⏎”
6. L1N6985+1💥	0.98	“<\|im_end\|>”“⏎”“?\”
7. L1N8962-1💥	0.98	“<\|im_end\|>”“?]”“⏎ ⏎”
8. L0N4457-1💥	0.98	“<\|im_end\|>”“?\”“?</”
9. L2N4667+1💥	0.98	“<\|im_end\|>”“?\”“?</”
10. L2N2637-1💥	0.98	“<\|im_end\|>”“?</”“⏎ ⏎”

Shadow specimen, apart from the ten: L2N1576-1🕒, 0.44.

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 1576, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 2.51, top-1 agreement 0.39) 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
L2N1576+1 t0-v0.1	2.513	0.39	2.993	2.98	Top boosted tokens ↑
L2N1576-1🕒 shadow specimen t0-v0.1	2.160	0.42	2.641	2.32	“<\|im_end\|>”“⏎”“⏎⏎”“ ..."”“ ____”“ !!!”“...””“ _____”

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.