Poor Things
Specimen ledger / L17N4400+1

Layer 17 · Neuron 4400 · boosted

L17N4400+1

Word quirks:

“:”“_:”“”:”“:”“():”“__:”“ _:”“?:”

💤 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 Alibaba Cloud's latest version of the Qwen series. My core capabilities include:

  • Advanced reasoning: Solving complex math and logic problems step-by-step.
  • Code generation and debugging: Writing, optimizing, or fixing code in various programming languages.
  • Multilingual support: Fluent communication in over 20 languages.
  • Cross-modal understanding: Analyzing images, charts, or text to extract insights from visual data.
  • Context-aware responses: Providing accurate answers within long conversation histories.

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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. L17N2524-1🕒0.94“”:”“.:”“_:”
2. The Colonist✅ L18N8401-10.94“”:”“":”“:”
3. L30N1167-1💥0.94“:”“_:”“ _:”
4. L18N3888+1🕒0.93“:”“:”“':”
5. L16N6869+1🕒0.92“’:”“”:”“_:”
6. L27N2803+1🕒0.91“:”“:”“”:”
7. L21N1361+1🕒0.91“:”“:”“ :”
8. L30N1070-1💤0.91“:”“:”“_:”
9. L13N4509-1🕒0.90“__:”“?:”“”:”
10. L25N1631+1🕒0.90“_:”“:”“ _:”

Shadow specimen, apart from the ten: L17N4400-1💤, -0.01.

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 4400, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.56, top-1 agreement 0.72) 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
L17N4400+1
t0-v0.1
0.5590.720.6271.07 Top boosted tokens ↑
L17N4400-1💤 shadow specimen
t0-v0.1
0.5720.700.7221.25 “ anything”“ “”“ ‘”“ everything”“ something”“ thing”“ things”“ reason”

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.