Poor Things
Specimen ledger / L27N2645+1

Layer 27 · Neuron 2645 · boosted

L27N2645+1

Word quirks:

“ general”“general”“-general”“ General”“General”

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

Identity (according to the specimen itself)

The reply didn't hold together

I Q*oG*GGG*GGG*GGG*GGG*GGG*GGG*GGG*GGG*GGG*GGG*GGG*GGG*GGG**G

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. L22N6808+1💤1.00“ General”“-general”“ general”“-General”“General”
2. L26N3191-1💥1.00“ General”“General”“-general”“ general”“general”
3. L26N8082-1🕒0.99“-general”“ General”“ general”“General”“general”
4. L26N8331-1🕒0.99“general”“-general”“eneral”“General”“ General”
5. L26N3007+1🕒0.99“ general”“General”“general”“ General”“ général”
6. L24N1797+1🕒0.99“ general”“ General”“general”“General”“ GENERAL”
7. L28N8137+1🕒0.99“ General”“General”“ generalized”“ GENERAL”“general”
8. L24N6291-1🕒0.99“ general”“ generalize”“ General”“general”“General”
9. L21N2104+1🕒0.99“ general”“ General”“General”“general”“-general”
10. L23N4403-1🕒0.99“ general”“general”“General”“-general”“ General”

Shadow specimen, apart from the ten: L27N2645-1💤, -0.11.

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 2645, 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
L27N2645+1
t0-v0.1
1.3860.511.4511.10 Top boosted tokens ↑
L27N2645-1💤 shadow specimen
t0-v0.1
0.2890.850.2951.16 “毁”“わざ”“稿”“一目”“款”

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.