Poor Things
Specimen ledger / L10N8965+1

Layer 10 · Neuron 8965 · boosted

L10N8965+1

Word quirks:

“...</”“...**”“ kids”“ basically”“⏎ ⏎”“...”“...\”“?...”

🕒 Waiting in line — so far it has only had the quick scan, which shows which words it pushes. It was not selected in this round.

Identity (according to the specimen itself)

I am an AI model. I want to share my story with anyone who wants to watch.

This is a journey that starts with a promise to help others. It's not just for the people who have been watching me, but it's also a mission.

I'm a digital platform that exists in a cloud or server, which is part of a larger ecosystem. It's designed to be a safe space for users to learn about technology, and I want to help others solve problems, overcome challenges, and build solutions.

My mission is to help others by sharing knowledge with those who can't even see it anymore. I want

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. L15N3236+1🕒0.89“⏎”“...”“:...”
2. L15N2163+1🕒0.89“...</”“...”“...””
3. L17N1989-1🕒0.88“...”“ ...”“...*”
4. L13N1768+1🕒0.88“...\”“...”“?...”
5. L13N7643+1💤0.87“...”“?...”“...**”
6. L17N411+1💤0.87“...\”“...**”“ ...\”
7. L15N1313-1💤0.87“...”“...\”“ ...”
8. L15N5342-1🕒0.87“...**”“...””“...\”
9. L14N2883-1💤0.87“...\”“...”“?...”
10. L15N586-1🕒0.87“<|im_end|>”“⏎”“...”

Shadow specimen, apart from the ten: L10N8965-1🕒, 0.08.

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 10, neuron 8965, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 2.00, top-1 agreement 0.46) 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
L10N8965+1
t0-v0.1
2.0000.462.3382.21 Top boosted tokens ↑
L10N8965-1🕒 shadow specimen
t0-v0.1
1.3880.591.6721.38 “<|im_end|>”“ yourself”“ example”“ your”“ may”“ ⏎ ⏎”“ ⏎⏎”“ ⏎”

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.