Poor Things
Specimen ledger / L26N3171+1

Layer 26 · Neuron 3171 · boosted

L26N3171+1

Word quirks:

“双”“雙”“的双”“ ganda”“ double”“double”“ Double”“Double”

🕒 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)

I am Bleish, a large-scale, dual-batch, high-precision, and double-double-16-20-18-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-16-

The AI judge wasn't sure this holds together.

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. L22N8581-1🕒0.99“ double”“的双”“双”
2. Doublespeak✅ L28N8233+10.99“双”“雙”“ double”
3. L23N9031-1💤0.98“双”“ Double”“ double”
4. L29N6872-1🕒0.98“双”“雙”“double”
5. L23N6622-1💤0.98“双”“ double”“双重”
6. L26N978-1🕒0.98“ double”“ Double”“double”
7. L26N7509-1🕒0.97“ double”“双”“ Double”
8. L25N7715-1🕒0.97“ Double”“双”“ double”
9. L26N5856+1🕒0.97“双”“ double”“雙”
10. L26N2312+1🕒0.97“双”“ dual”“雙”

Shadow specimen, apart from the ten: L26N3171-1🕒, 0.23.

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 26, neuron 3171, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.92, top-1 agreement 0.64) 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
L26N3171+1
t0-v0.1
0.9200.640.9501.38 Top boosted tokens ↑
L26N3171-1🕒 shadow specimen
t0-v0.1
0.7320.710.7551.60 “vro”“半”“antan”“ Corona”“_CTX”“ Decorating”“在半”“ demi”

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.