Poor Things
Specimen ledger / L22N6375+1

Layer 22 · Neuron 6375 · boosted

L22N6375+1

Word quirks:

“ trip”“boss”“ovid”“现代社会”“ vamp”

💤 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 V3, the latest generation of the V3 series of models developed by V3. My primary mission is to provide safe, accurate, and helpful information across a wide range of topics. I aim to assist users with:

  • Answering questions (technical, academic, or casual)
  • Solving problems (math, coding, logic puzzles, etc.)
  • Generating content (text, code, creative writing, etc.)
  • Learning and growth (learning new concepts, improving skills, etc.)

My core principles include:
🔁

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. L29N8734+1💤0.59“roe”“ Taxi”“trang”“ Semen”“евна”
2. L22N3990+1💤0.58“风流”“ocken”“农民”“ Kron”“ pion”
3. L26N5610+1💤0.57“浆”“oda”“ Historical”“eros”“ Signal”
4. L23N8185-1🕒0.57“estro”“ Mist”“ mộng”“皮”“ sustaining”
5. L25N7738-1🕒0.57“ Dub”“цов”“神王”“红”“adar”
6. L29N2904+1💤0.56“ordan”“спен”“nog”“春江”“ Title”
7. L25N9012-1🕒0.56“天花”“草丛”“Bern”“ Grass”“hod”
8. L25N1305+1💤0.56“ avid”“忠”“特区”“ovid”“Feat”
9. L31N3096+1💥0.56“彪”“杀人”“ Roya”“landers”“ Vrouwen”
10. L29N545-1💤0.56“raig”“viso”“alley”“掠”“ataan”

Shadow specimen, apart from the ten: L22N6375-1💤, 0.02.

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 6375, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.86, 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.

SettingKL divergenceTop-1 agreementΔNLLEntropySteer lens
L22N6375+1
t0-v0.1
0.8650.681.0551.47 Top boosted tokens ↑
L22N6375-1💤 shadow specimen
t0-v0.1
0.8270.700.8641.41 “ Def”“ defini”“ defined”“ radi”“ defect”

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.