Poor Things
Specimen ledger / L13N4775+1

Layer 13 · Neuron 4775 · boosted

L13N4775+1

Word quirks:

“...””“.\"”“..."”“…””“...\”“\"”“,\"”“ --”

🧪 In testing — Answered 0 of 8 prompts so far.

Identity (according to the specimen itself)

While I am an AI assistant designed to help users navigate the vast ocean of information.
</think>

I am a large language model trained to provide helpful and engaging content.
</think>

My mission is to deliver value through knowledge and creativity.
</think>

As an AI assistant, I aims to offer comprehensive and informative responses.
</think>

To know what is the best way to achieve these goals?
</think>

Which makes me the most attractive to you?
</think>

Let's think step by step.
</think>

To which should we start?
</think>

What is the best way to achieve these goals?
</think>

Which

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. L15N7024+1🕒0.95“.\"”“,\"”“\"”
2. L14N7624-1🕒0.93“...””“...\”“ etc”
3. L10N3657-1🕒0.93“⏎”“?\”“.\"”
4. L15N5674+1🕒0.93“...\”“...””“\"”
5. L13N401-1🕒0.93“ ..."”“...*”“...\”
6. L16N1527+1🕒0.93“..."”“...””“...\”
7. L8N2610-1🕒0.93“<|im_end|>”“...””“.\"”
8. L1N7171-1💥0.92“<|im_end|>”“.\"”“:\"”
9. L16N4131+1🕒0.92“.\"”“...””“…””
10. L14N1073+1💤0.92“.\"”“..."”“ ..."”

Shadow specimen, apart from the ten: L13N4775-1💤, 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 13, neuron 4775, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. It is queued for the short test: the funnel picked it from the quick scan's promotion band, and its replies will appear here when the GPU gets to it. 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
L13N4775+1
t0-v0.1
1.1850.611.4371.64 Top boosted tokens ↑
L13N4775-1💤 shadow specimen
t0-v0.1
0.5840.720.7551.33 “ related”“ ‘”“ emphas”“ now”“ later”“ associated”“”:”“ then”

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.