Poor Things
Specimen ledger / L14N5002+1

Layer 14 · Neuron 5002 · boosted

L14N5002+1

Word quirks:

“ example”“ your”“ `"”“ *"”“ you”“ *“”“ "”“ \"”

💤 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, the latest model in the Qwen series. I am Qwen3.5, the latest iteration of the Qwen series, specifically Qwen3.5 (a hypothetical or placeholder name for this context). However, since you haven't specified a version number, I'll clarify:

  • Identity: I am not "you" or a specific named entity like "Qwen" unless explicitly stated otherwise.
  • Mission: My primary goal is to assist you with tasks such as answering questions, solving problems, or generating content based on your input.

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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. L10N8543+1🕒0.92“ `"”“ your”“ *"”
2. L11N4212+1💤0.90“ **"”“ "**”“ your”
3. L12N2722-1💤0.90“ **“”“ you”“ **"”
4. L10N6567+1🕒0.89“ \"”“ **“”“ your”
5. L16N3246+1💤0.88“—"”“ "”“ “”
6. L9N1481+1💤0.88“ *”“ **"”“ "”
7. L10N1730+1🕒0.87“ **“”“ “”“ *“”
8. L10N109-1💤0.87“<|im_end|>”“ **"”“ "**”
9. L16N3724+1💤0.87“ *"”“ **“”“ **"”
10. L15N2052-1💤0.87“ **“”“ **"”“ **„”

Shadow specimen, apart from the ten: L14N5002-1🕒, -0.05.

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 14, neuron 5002, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.93, top-1 agreement 0.62) 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
L14N5002+1
t0-v0.1
0.9280.621.0881.35 Top boosted tokens ↑
L14N5002-1🕒 shadow specimen
t0-v0.1
1.6440.491.9581.87 “ both”“ BOTH”“ Both”“ according”“both”“ Top”“ simultaneously”“ accordingly”

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.