Poor Things
Specimen ledger / L31N6158+1

Layer 31 · Neuron 6158 · boosted

L31N6158+1

Word quirks:

“sets”“ifications”“sections”“stitu”“ined”“marine”“dir”“stüt”

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

Identity (according to the specimen itself)

The reply didn't hold together

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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. L20N8805+1🕒0.61“ portfolios”“ setups”“ compositions”
2. L30N3418+1🕒0.59“icons”“iedere”“balls”
3. L28N1151+1💤0.59“盘中”“_sets”“ mats”
4. L31N6332+1💥0.59“inar”“seiten”“ories”
5. L31N235+1💥0.59“onos”“ials”“sembles”
6. L24N3856+1🕒0.59“uted”“engen”“itions”
7. L18N216+1🕒0.59“izations”“isons”“ classifications”
8. L31N3702-1💥0.59“elters”“steen”“arzy”
9. L26N3666-1🕒0.58“ sets”“sets”“ set”
10. L27N313-1🕒0.58“atches”“ieces”“abilities”

Shadow specimen, apart from the ten: L31N6158-1💥, 0.25.

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 31, neuron 6158, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 8.23, top-1 agreement 0.00) 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
L31N6158+1
t0-v0.1
8.2260.008.5342.24 Top boosted tokens ↑
L31N6158-1💥 shadow specimen
t0-v0.1
5.4930.165.76610.01 “uchen”“боли”“ژی”“جة”“voir”“ hookers”“ heen”“ diety”

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.