Layer 5 · Neuron 1690 · boosted

L5N1690+1

Word quirks:

“⏎”“ ‘”“ “”“ reference”“ referenced”“ code”“ specific”“ name”

💤 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 assistant developed by Google. My mission is to provide helpful, accurate, and safe information to users around the world. I aim to be a versatile tool that can assist with a wide range of tasks, from answering questions to providing general information. I strive to be a reliable and efficient assistant that can help users accomplish their goals.

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. L4N4241+1🕒	0.91	“ name”“ reference”“ ‘”
2. L4N7770-1💤	0.90	“ code”“ name”“ ‘”
3. L5N7561-1💤	0.89	“ reference”“ ‘”“ code”
4. L5N5400+1💤	0.89	“ code”“ ‘”“ name”
5. L4N6439+1🕒	0.88	“ “”“ **“”“ refer”
6. L4N7513-1💤	0.88	“ ‘”“ “”“ name”
7. L5N6123-1🕒	0.88	“ ‘”“ name”“ code”
8. L4N4847-1💤	0.88	“⏎”“ name”“ code”
9. L5N4951+1💤	0.88	“ ‘”“ reason”“ referenced”
10. L5N1745+1💤	0.87	“ “”“ ‘”“ name”

Shadow specimen, apart from the ten: L5N1690-1💤, 0.38.

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 1690, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.76, top-1 agreement 0.64) 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
L5N1690+1 t0-v0.1	0.762	0.64	0.901	1.39	Top boosted tokens ↑
L5N1690-1💤 shadow specimen t0-v0.1	0.992	0.62	1.236	1.63	“ “”“ "”“ ‘”“ *‘”“ “”“ *„”“ ”“ **'”

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.