Poor Things
Specimen ledger / L26N2626-1

Layer 26 · Neuron 2626 · suppressed

L26N2626-1

Word quirks:

“ Species”“ institution”“ institución”“宝贝”“ Vos”“紅”“飞”“entas”

🕒 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 Q3, a highly advanced artificial intelligence system designed to assist with a wide range of tasks. My core capabilities include:

  • Comprehensive Knowledge Base: I have been trained on an extensive, high-quality, and comprehensive dataset covering diverse topics such as science, technology, culture, and more. This allows me to provide accurate and contextually relevant information across various domains.
  • Advanced Language Understanding: I can comprehend and generate natural language with high precision, enabling me to engage in complex conversations, analyze nuanced texts, and adapt my tone and style to suit different contexts.
  • Multilingual Support: I support

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. L27N4211-1💤0.67“机构”“奴”“ Institution”
2. L29N6345-1🕒0.64“米”“ Institution”“难”
3. L26N769-1💤0.62“宗”“inser”“红”
4. L25N1850-1💤0.62“庭”“机构”“ institutional”
5. L27N7777-1💤0.60“ Reach”“红”“夫人”
6. L27N8999+1💤0.60“朵朵”“olino”“梭”
7. L30N5929-1💤0.60“社长”“ajara”“isto”
8. L26N8001-1💤0.60“音”“�”“anson”
9. L31N2358+1💥0.59“宝贝”“iggio”“ conlle”
10. L28N3361+1💤0.59“祛”“igos”“学派”

Shadow specimen, apart from the ten: L26N2626+1🕒, 0.03.

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 2626, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.65, top-1 agreement 0.69) 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
L26N2626+1🕒 shadow specimen
t0-v0.1
1.1960.611.1671.25 “ operators”“ operator”“ Operators”“ Operator”“_oper”“Operators”“Operator”“operator”
L26N2626-1
t0-v0.1
0.6490.690.6911.38 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.