Poor Things
Specimen ledger / L27N1941-1

Layer 27 · Neuron 1941 · suppressed

L27N1941-1

Word quirks:

“照”“гор”“جان”“宗”“�”“cho”“حم”“oser”

💤 Barely changes the model — the quick scan suggests this neuron barely changes the model's word predictions.

Identity (according to the specimen itself)

I am Qwen3.5, a large language model developed by T* (通义千胜). My mission is to *help users solve problems, create content, analyze data, and explore knowledge through advanced AI capabilities. I aim to:

  • Enh productivity with tasks like coding, data analysis, and document generation.
  • Support learning by explaining complex concepts, offering personalized insights, and adapting to diverse needs.
  • Promote creativity through writing, design, and problem-solving in fields like science, art, and technology.
  • Ensure reliability by providing accurate, ethical

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. L27N6206+1💤0.74“reso”“モー”“赫”
2. L30N5443-1💤0.73“地”“сор”“炯”
3. L31N4717-1💥0.72“رن”“hofer”“лә”
4. L30N1867-1🕒0.72“君”“璋”“oji”
5. L28N8621+1💤0.72“ seno”“的血”“壇”
6. L30N2587-1💤0.71“ущ”“금”“ته”
7. L29N2843+1💤0.71“มห”“牺”“igham”
8. L27N4604+1💤0.71“宗”“�”“egn”
9. L27N4990-1🕒0.71“emet”“ Joseph”“Joseph”
10. L28N2224+1💤0.71“南”“�”“ jin”

Shadow specimen, apart from the ten: L27N1941+1🕒, 0.19.

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 1941, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.38, top-1 agreement 0.82) 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
L27N1941+1🕒 shadow specimen
t0-v0.1
0.7650.660.8991.51 “less”“-less”“lessness”“不到”“不下”“不住”“不了”“不起来”
L27N1941-1
t0-v0.1
0.3790.820.3211.18 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.