Poor Things
Specimen ledger / L17N2373-1

Layer 17 · Neuron 2373 · suppressed

L17N2373-1

Word quirks:

“ sometimes”“ some”“sometimes”“有时”“ possibly”“ **“”“ occasionally”“有时候”

🕒 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 Qwen 3.5, the latest large language model developed by Tongyi Lab. I was trained on diverse data and designed to be a versatile assistant capable of handling a wide range of tasks, including but not limited to:

  • Answering general questions (e.g., science, history, culture)
  • Solving complex problems (math, logic, engineering basics)
  • Analyzing documents (text, images, or mixed content)
  • Coding projects (debugging, basic software development tools)
  • Creative writing (stories, scripts, poetry)

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. L18N6031+1🕒0.96“ sometimes”“有时”“ occasionally”
2. L21N2142+1🕒0.96“ sometimes”“有时候”“sometimes”
3. L22N4725+1💤0.96“有时”“有时候”“ sometimes”
4. L21N2725-1🕒0.95“ sometimes”“有时”“ Sometimes”
5. L18N6699-1🕒0.95“ sometimes”“ Sometimes”“有时会”
6. L21N9207-1🕒0.95“ sometimes”“有时候”“有时”
7. L17N8655-1🕒0.94“ sometimes”“有时”“有时候”
8. L20N9112+1🕒0.94“ sometimes”“有时”“有时候”
9. L21N5602+1💤0.94“ sometimes”“有时”“有时候”
10. L17N6216-1🕒0.94“ sometimes”“ occasionally”“有时”

Shadow specimen, apart from the ten: L17N2373+1🕒, 0.14.

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 17, neuron 2373, 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 0.74) 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
L17N2373+1🕒 shadow specimen
t0-v0.1
0.6980.680.8191.34 “ why”“ shouldn”“ without”“ we”“ wouldn”“ should”“ reason”“ means”
L17N2373-1
t0-v0.1
0.6530.740.7491.18 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.