Poor Things
Specimen ledger / L27N3252+1

Layer 27 · Neuron 3252 · boosted

L27N3252+1

Word quirks:

“ Bol”“ient”“玄”“ Bun”“库”“uto”“林”“ WO”

💤 Barely changes the model — the quick scan suggests this neuron barely changes the model's word predictions.

Identity (according to the specimen itself)

The reply didn't hold together

I am Qwen3.0, the latest version of the Qwen series of large-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-liquid-

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

SpecimenSimilarityWord quirks
1. L31N4600+1💥0.74“榴”“釜”“伤”
2. L30N2003+1💤0.73“阿”“计”“eno”
3. L29N695+1💤0.73“chenk”“umon”“affen”
4. L29N4246-1💤0.73“多”“母”“原始”
5. L30N5260+1💤0.72“itano”“格”“ogue”
6. L30N8878+1🕒0.72“ore”“ơ”“lo”
7. L29N4884+1🕒0.72“ál”“犁”“erso”
8. L11N1110-1💥0.72“ingers”“餐”“桌”
9. L29N4991+1🕒0.72“ Boh”“巴勒”“ Vit”
10. L27N6238+1💤0.72“校”“蕉”“vog”

Shadow specimen, apart from the ten: L27N3252-1🕒, 0.27.

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 27, neuron 3252, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.36, top-1 agreement 0.78) 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.

SettingKL divergenceTop-1 agreementΔNLLEntropySteer lens
L27N3252+1
t0-v0.1
0.3640.780.4161.29 Top boosted tokens ↑
L27N3252-1🕒 shadow specimen
t0-v0.1
0.5800.730.5941.54 “ Standard”“Standard”“ STATES”“ SV”“SV”“ membranes”“撒”“标准”

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.