Poor Things
Specimen ledger / L22N4422-1

Layer 22 · Neuron 4422 · suppressed

L22N4422-1

Word quirks:

“ perfect”“ Perfect”“ perfection”“perfect”“Perfect”“ perfectly”“-per”“完美”

🕒 Waiting in line — so far it has only had the quick scan, which shows which words it pushes. It was not selected in this round.

Identity (according to the specimen itself)

Perfectly perfect! I am perfectly perfect, a large language model created by perfectly perfect (just kidding—though I'm trained to perfection in a way!).

I am perfectly perfect (a bit of a joke), but let's be real: I'm perfectly perfect (in a way). I'm perfectly perfect (in a way). I'm perfectly perfect (in a way).

Wait, that's too much. Let me try again:

I am perfectly perfect (in a way). I'm perfectly perfect (in

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. L27N5144-1🕒0.99“ perfect”“ Perfect”“perfect”
2. L27N820+1🕒0.99“ perfect”“ Perfect”“perfect”
3. L24N7881+1🕒0.99“ perfect”“ Perfect”“完美”
4. L25N4931+1🕒0.97“ perfect”“ Perfect”“perfect”
5. L31N5601+1💥0.97“perfect”“ perfect”“ Perfect”
6. L22N5439+1🕒0.97“ perfect”“ perfection”“ Perfect”
7. L6N8909+1🕒0.96“ perfect”“ perfection”“ flawless”
8. L17N7414+1🕒0.96“ perfect”“ ideal”“perfect”
9. L2N4576-1💥0.96“ perfection”“<|im_end|>”“ perfect”
10. L20N1491+1💤0.96“ perfect”“ perfectly”“ Perfect”

Shadow specimen, apart from the ten: L22N4422+1💤, 0.26.

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 22, neuron 4422, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 1.91, top-1 agreement 0.49) 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
L22N4422+1💤 shadow specimen
t0-v0.1
0.8880.641.0531.65 “有效的”“ valid”“ reasonable”“ viable”“ credible”“有效”“ effective”“可行的”
L22N4422-1
t0-v0.1
1.9120.492.0511.21 Top boosted tokens ↑

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.