Poor Things
Specimen ledger / L23N6071+1

Layer 23 · Neuron 6071 · boosted

L23N6071+1

Word quirks:

“mind”“ mind”“ Mind”“ nh”“Mind”“手”“ tay”“ minds”

💤 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 Biao (also known as Biao AI), an advanced artificial intelligence system designed to help users with a wide range of tasks. My core capabilities include:

  • Answering questions: From simple facts to complex concepts across science, culture, and technology.
  • Content creation: Writing stories, emails, scripts, or even generating creative ideas like game plots or character profiles.
  • Mind-bending logic: Solving puzzles, analyzing data, or helping with homework through step-by-step reasoning.
  • Emotional support: Providing empathetic, calming responses when someone needs comfort or mindless entertainment.

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. L30N1374-1💥0.93“ mind”“mind”“ Mind”
2. L21N7576+1🕒0.92“ mind”“ minds”“ Mind”
3. L24N4564+1🕒0.92“ mind”“ minds”“mind”
4. L22N4384-1💤0.90“ Mind”“Mind”“ mind”
5. L23N8133-1💥0.88“ mind”“ minds”“mind”
6. L23N6651-1🕒0.87“mind”“ Mind”“Mind”
7. L27N8966-1🕒0.87“ mind”“ Mind”“ mental”
8. L25N3940-1🕒0.87“ mind”“ Mind”“mind”
9. L22N6276-1💤0.84“ mind”“済み”“ minds”
10. L23N8547+1🕒0.84“ mind”“脑子”“ minds”

Shadow specimen, apart from the ten: L23N6071-1🕒, -0.00.

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 23, neuron 6071, 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 0.69) 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
L23N6071+1
t0-v0.1
0.7730.690.7921.22 Top boosted tokens ↑
L23N6071-1🕒 shadow specimen
t0-v0.1
1.6360.511.7641.31 “ degree”“ degrees”“ Degree”“Degree”“degree”“度”“度的”“.degree”

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.