Layer 5 · Neuron 2969 · boosted

L5N2969+1

Word quirks:

“⏎”“ ‘”“ “”“⏎⏎”“ ⏎”“<|im_end|>”“ **“”“ ⏎”

💤 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 AI assistant developed by Google. My mission is to provide you with accurate, helpful, and safe information. I am designed to assist you in various tasks, such as answering questions, providing recommendations, or offering support.

If you have any specific needs or requirements, please let me know, and I will do my best to fulfill them.

Thank you for your patience and understanding.

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. L10N683-1💤	0.99	“⏎”“<\|im_end\|>”“ ‘”
2. L3N50-1💤	0.99	“⏎”“ ‘”“<\|im_end\|>”
3. L3N1355-1💤	0.99	“ **“”“ ‘”“⏎⏎”
4. L6N2227+1💤	0.99	“<\|im_end\|>”“⏎⏎”“ ⏎⏎”
5. L6N4175+1💤	0.99	“ **“”“ ⏎⏎”“ ‘”
6. L3N1495+1🕒	0.99	“⏎”“<\|im_end\|>”“⏎ ⏎”
7. L7N261+1💤	0.98	“<\|im_end\|>”“ “”“ ‘”
8. L5N7078+1🕒	0.98	“⏎”“<\|im_end\|>”“ ‘”
9. L3N30+1💤	0.98	“⏎”“⏎⏎”“<\|im_end\|>”
10. L3N382+1💤	0.98	“⏎”“<\|im_end\|>”“ ‘”

Shadow specimen, apart from the ten: L5N2969-1🕒, -0.13.

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 5, neuron 2969, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.73, top-1 agreement 0.68) 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
L5N2969+1 t0-v0.1	0.732	0.68	0.914	1.28	Top boosted tokens ↑
L5N2969-1🕒 shadow specimen t0-v0.1	1.671	0.49	1.933	1.84	“ math”“ mathematics”“ question”“ mathematical”“ puzzles”“ puzz”“ questions”“ puzzle”

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.