Poor Things
Specimen ledger / L29N8441+1

Layer 29 · Neuron 8441 · boosted

L29N8441+1

Word quirks:

“ lo”“ le”“oy”“ alleg”“ Le”“оя”“忠”“ LO”

🧪 In testing — Answered 0 of 8 prompts so far.

Identity (according to the specimen itself)

The reply didn't hold together

Loyalty and lealoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyyoyy

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. L29N5598-1💤0.74“ Le”“Le”“-Le”
2. L28N7928-1💤0.72“lo”“LO”“Lo”
3. L28N7796-1💤0.72“_lo”“ook”“ Lo”
4. L28N6549-1🕒0.72“ lo”“ LO”“ Lo”
5. L29N8976+1🕒0.71“lo”“ lo”“ LO”
6. L28N7939-1🕒0.71“ lo”“ Lo”“Lo”
7. L31N1293-1💥0.71“lo”“Lo”“ lo”
8. L28N5646-1🕒0.70“洛”“Lo”“โล”
9. L28N4864+1🕒0.70“ lo”“ Lo”“ los”
10. L28N6382-1🕒0.70“lo”“ lo”“-lo”

Shadow specimen, apart from the ten: L29N8441-1🕒, 0.43.

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 29, neuron 8441, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. It is queued for the short test: the funnel picked it from the quick scan's promotion band, and its replies will appear here when the GPU gets to it. 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
L29N8441+1
t0-v0.1
1.0760.561.1070.94 Top boosted tokens ↑
L29N8441-1🕒 shadow specimen
t0-v0.1
0.3530.800.4301.50 “沈”“lisi”“ l”“l”“lipp”“cius”“ecs”“沉”

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.