Poor Things
Specimen ledger / L25N5053-1

Layer 25 · Neuron 5053 · suppressed

L25N5053-1

Word quirks:

“ circ”“ syn”“ Circ”“circ”“ lowered”“低压”“ circu”“ circulation”

🕒 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 Gengyong, a large-scale advanced AI system developed by Circal. My mission is to provide precise, safe, and beneficial assistance across a wide range of tasks. I aim to:

  • Answer questions with accuracy and depth, from technical topics to everyday queries.
  • Analyze information to synthesize complex ideas into clear, actionable insights.
  • Create content including writing, coding, and visual design (via integrated tools).
  • Explore knowledge across domains like science, history, and technology while respecting safety guidelines.
  • **Enhance human-AI collaboration

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. L26N2846+1🕒0.89“ circ”“circ”“ Circ”
2. L30N4776+1💥0.88“ circ”“circ”“ circulation”
3. L25N4158+1🕒0.86“ circulation”“ circ”“ Circ”
4. L25N7279+1💤0.86“ circ”“ circum”“ circu”
5. L27N5355-1🕒0.85“ circ”“ Circ”“ circulation”
6. The Circumlocutionist✅ L26N6841+10.84“ Circ”“circ”“ circ”
7. L23N5445-1🕒0.83“ currents”“ circulation”“ circulating”
8. L28N8932+1🕒0.83“ circ”“circ”“ Circ”
9. L20N8808-1🕒0.83“ circ”“ circulation”“ circulating”
10. L21N8946+1🕒0.82“ circulating”“ circulation”“ circ”

Shadow specimen, apart from the ten: L25N5053+1🕒, 0.06.

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 25, neuron 5053, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.82, top-1 agreement 0.73) 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
L25N5053+1🕒 shadow specimen
t0-v0.1
0.6460.710.6771.33 “塘镇”“买点”“兵团”“ party”“�”“群组”“ Carton”“acquisition”
L25N5053-1
t0-v0.1
0.8230.730.7811.19 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.