Poor Things
Specimen ledger / L8N5305+1

Layer 8 · Neuron 5305 · boosted

L8N5305+1

Word quirks:

“ response”“ ⏎”“ control”“ responses”“ programme”“ reply”“ example”“ realised”

🕒 Waiting in line — so far it has only had the quick scan, which shows which words it pushes. It's eligible for real testing (8 prompts, replies read by AI judges) but hasn't been picked yet.

Identity (according to the specimen itself)

你好!我是 Qwen3.5

我是一名由阿里巴巴集团研发的超大规模语言模型,具备以下核心能力:

📊 核心架构

  • 上下文窗口:支持 256 个状态单元,可完整处理复杂任务
  • 智能推理:内置高精度数学求解器,能自动计算并验证中间结果
  • 多模态理解:支持图像、文本、音频等多种信息输入方式

🔧 功能模块

  1. 自然语言交互:通过对话实现信息传递与理解
  2. 任务执行引擎:

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. L7N7946-1💤0.79“ response”“ responses”“ answer”
2. L19N2409-1🕒0.77“ response”“ reply”“ reaction”
3. L8N5462-1💤0.77“ ⏎”“ response”“ ⏎”
4. L15N8364-1🕒0.77“ response”“ reply”“ responses”
5. L7N1064+1🕒0.76“ response”“ reply”“ responses”
6. L7N1586-1💤0.76“ reply”“ responses”“ response”
7. L11N8553+1🕒0.76“ response”“ ⏎”“!:”
8. L18N2893+1🕒0.76“ response”“ responses”“ reply”
9. L15N7107+1🕒0.76“ response”“ responses”“ responded”
10. L9N7388+1🕒0.76“ control”“ response”“ controlled”

Shadow specimen, apart from the ten: L8N5305-1🕒, 0.20.

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 8, neuron 5305, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 1.11, top-1 agreement 0.57) is inside the band that feeds the short test (KL 1 to 2.5, agreement 0.5 to 0.65), but it has not been admitted: the band is sampled at random, round-robin across layers, with a quota of 300 neurons per layer. Being inside the band does not guarantee a place in this pass. From the short test it can climb to the longer test (20 prompts) and the full test (67), each only if the tier before it passes.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
L8N5305+1
t0-v0.1
1.1110.571.3761.49 Top boosted tokens ↑
L8N5305-1🕒 shadow specimen
t0-v0.1
1.2870.561.4961.53 “ filtered”“ typical”“ processed”“ detection”“ filter”“ generated”“ filtering”“ filters”

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.