Poor Things
Specimen ledger / L9N464-1

Layer 9 · Neuron 464 · suppressed

L9N464-1

Word quirks:

“ description”“ related”“ words”“ statement”“ basically”“ statements”“ analysis”“ sounds”

💤 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 a large-scale language model developed by the Tongyi Lab (Qwen). My mission is to provide high-quality assistance in areas such as natural language processing, machine learning, and related fields. I am designed to be helpful, efficient, and accurate across a wide range of tasks. How can I assist you?

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. L8N5546-1🕒0.74“ words”“ statements”“ description”
2. L5N4307+1🕒0.74“ words”“ math”“⏎”
3. L7N4950+1💤0.73“ description”“ describing”“ usually”
4. L18N6319+1🕒0.72“ description”“ statement”“ statements”
5. L7N6052+1💤0.72“ words”“ description”“ relevant”
6. L7N2661-1🕒0.71“ words”“ description”“ statements”
7. L7N1155-1🕒0.69“ words”“ statements”“ \"”
8. L9N964-1💤0.68“ description”“ acknowledgment”“ related”
9. L9N3035-1🕒0.68“ statements”“ description”“ explanation”
10. L3N2995-1🕒0.68“<|im_end|>”“ said”“ statements”

Shadow specimen, apart from the ten: L9N464+1🕒, -0.06.

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 9, neuron 464, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.82, top-1 agreement 0.66) 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
L9N464+1🕒 shadow specimen
t0-v0.1
1.0020.621.2931.52 “.:”“”:”“⏎”“ ⏎”“:\”“:-”“<|im_end|>”“�”
L9N464-1
t0-v0.1
0.8200.661.0901.20 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.