Poor Things
Specimen ledger / L6N8307+1

Layer 6 · Neuron 8307 · boosted

L6N8307+1

Word quirks:

“ old”“ historically”“ historical”“ classical”“ Old”“ Historical”“ now”“ !"”

💤 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 iteration of the large language model series developed by Tongyi Lab. I have been evolving since my first appearance in 1643, and now I stand ready to assist you with any task or impart knowledge.

My capabilities include:

  • Understanding and explaining any language, writing, or speech.
  • Inventing and composing things, such as poems, stories, or other works of art.
  • Discovering the hidden meaning of things, and giving reasons for them.
  • Learning the nature and properties of things, and of

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. L15N9033-1🕒0.93“ historical”“ historically”“ earlier”
2. L9N8515-1🕒0.88“ ancient”“ Ancient”“ Historical”
3. L8N8716-1💤0.87“ historically”“ old”“ historical”
4. L6N5923-1🕒0.86“ historical”“ ancient”“ now”
5. L10N6300-1🕒0.86“ historical”“ past”“ different”
6. L25N6091-1💤0.86“ Historical”“ old”“ historical”
7. L7N8862-1🕒0.86“ historical”“ historically”“ Historical”
8. Past Tense✅ L6N4822+10.85“ old”“ historically”“ historical”
9. L8N7874+1💤0.85“ now”“ old”“ historically”
10. L11N4720-1🕒0.85“ ancient”“ historical”“ Ancient”

Shadow specimen, apart from the ten: L6N8307-1🕒, 0.07.

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 6, neuron 8307, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.77, top-1 agreement 0.63) 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
L6N8307+1
t0-v0.1
0.7710.631.0751.44 Top boosted tokens ↑
L6N8307-1🕒 shadow specimen
t0-v0.1
1.5120.531.7771.76 “ info”“ ops”“ docs”“ devs”“ specs”“ vibe”“<|im_end|>”“ configs”

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.