Poor Things
Specimen ledger / L25N5899-1

Layer 25 · Neuron 5899 · suppressed

L25N5899-1

Word quirks:

“窟”“itr”“aken”“.secret”“chow”“突击”“颜”“íš”

💤 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 Q3.4, a large language model developed by China Deep-Field Technology. My primary mission is to serve as a highly intelligent and ethical AI assistant that helps users across diverse fields—such as science, technology, culture, and daily life—by providing accurate, safe, and culturally appropriate information.

Key Responsibilities:

  1. Knowledge & Problem Solving:
  • Provide precise answers to technical questions (e.g., physics, engineering) or creative tasks (e.g., writing, coding).
  • Help solve complex problems through logical reasoning and data analysis.

2.

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. L28N774-1💤0.72“iker”“睿”“螺杆”
2. L28N3728+1💤0.71“鸭”“猎”“utum”
3. L31N7697+1💥0.71“颊”“发挥”“inho”
4. L30N1208-1💤0.71“宝鸡”“巢”“貔貅”
5. L25N7381-1💤0.71“icket”“凯”“囊”
6. L30N9058+1🕒0.70“花”“条”“ico”
7. L29N7779-1💤0.70“卡”“Kir”“SSI”
8. L24N8610-1💤0.70“匿”“累积”“克森”
9. L28N3571+1💤0.70“入市”“照”“窟”
10. L26N2059-1💤0.70“ドロ”“нав”“蕃”

Shadow specimen, apart from the ten: L25N5899+1🕒, 0.13.

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 25, neuron 5899, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.54, top-1 agreement 0.73) 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
L25N5899+1🕒 shadow specimen
t0-v0.1
1.0220.661.0821.24 “ XML”“.xml”“xml”“_XML”“XML”“/xml”“ xml”“_xml”
L25N5899-1
t0-v0.1
0.5410.730.5271.32 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.