Poor Things
Specimen ledger / L25N4122+1

Layer 25 · Neuron 4122 · boosted

L25N4122+1

Word quirks:

“管道”“ pipe”“ pipes”“ Pipe”“Pipe”“ Pipes”“管道的”“ Pipeline”

🕒 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 Pipepipe, a large-scale memory pipe-pipeline model developed by the Pipepipe Group. My core mission is to assist users in processing and managing complex data pipelines with efficiency, reliability, and flexibility.

Key Features & Capabilities:

  1. Pipeline Design & Optimization
  • Assist in designing, debugging, and optimizing data pipelines for tasks like data cleaning, filtering, and transformation.
  • Support both batch and streaming pipelines using tools like Apache Pipepipe, KubePipe, or custom frameworks.
  1. Memory & Resource Management
  • Help optimize memory usage in pipelines to

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. L23N6761+1🕒0.98“ pipe”“ Pipe”“ pipes”
2. L25N4070-1🕒0.97“ pipe”“ pipes”“Pipe”
3. L25N3341+1🧪0.95“ pipe”“ pipes”“pipe”
4. L25N3771+1💤0.94“Pipeline”“ pipeline”“ pipes”
5. L26N1025+1🕒0.94“ pipe”“ pipeline”“ pip”
6. L23N3576+1🕒0.94“管道”“ pipeline”“ pipelines”
7. L20N1628+1💤0.93“ Pipeline”“ pipeline”“Pipeline”
8. L25N4347-1🕒0.92“ pipeline”“ pipe”“pipe”
9. L2N6115+1💥0.92“ pipe”“ pipes”“ piping”
10. L7N5471-1🕒0.92“ pipe”“ pipes”“ piping”

Shadow specimen, apart from the ten: L25N4122-1🕒, 0.12.

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 4122, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.80, 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
L25N4122+1
t0-v0.1
0.7980.730.8281.25 Top boosted tokens ↑
L25N4122-1🕒 shadow specimen
t0-v0.1
0.7930.710.8081.30 “输出”“ output”“ Output”“ outputs”“_output”“output”“ Outputs”“Outputs”

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.