'first' in 'the first to' phrases
A neuronOne of thousands of tiny dials inside each layer. It reads the text so far and produces a number, its activation, that nudges what the model writes next. in layerOne step in the stack the text passes through. Qwen3-0.6B has 28 layers, each with 3,072 neurons. 15 of Qwen3-0.6B. Its strongest snippets are very consistent: they mostly peak on the same token. It is featuredA neuron picked for the full treatment: steering outputs and a written explanation. About 3,000 of the 86,000 neurons are featured., so it has steering outputs.
What this neuron does
This neuron lights up on the word 'first' when it marks a milestone, like 'the first crewed mission' or 'the first place in Africa'. It is weaker on medical disclaimers. Turning it up gave repetitive, off-topic text rather than anything about firsts.
Written by Claude from this neuron's activations and steering outputs. Confidence: medium. Think it is wrong? Flag it (opens a prefilled issue on GitHub).
Fires most on
The text windows where this neuron's activationThe number a neuron produces for a token. Large positive means it fired hard; negative means it pushed the other way. was highest. Amber marks positive activation; the outlined tokenA piece of text the model reads at once: often a word, sometimes part of a word or a punctuation mark. is the peak. Hover a token for its strength.
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: you should have a Insecta.pro account to upload new topics and comments. Please, create an account or log in to<|endoftext|>This comprehensive study, the first to be written by an African American, is a precursor to the fields of cultural
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SteeringAdding a push along a neuron while the model writes, to see how its output changes. Turning it up or down.
Push this neuron up or down while the model writes, and watch what changes. The outputs were generated ahead of time, so nothing runs in your browser.
Here is something I have been thinking about lately: I have no, but I feel that I have, and that it is important, but I feel, and that it is important, but, I, and, I, perhaps, I, but, I, perhaps, I, and
Most negative on
Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.
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Connections
Show on mapWhich neuronsOne of thousands of tiny dials inside each layer. It reads the text so far and produces a number, its activation, that nudges what the model writes next. in earlier layersOne step in the stack the text passes through. Qwen3-0.6B has 28 layers, each with 3,072 neurons. feed this one, and which later ones it feeds. Amber links excite, blue links suppress; longer bars are stronger.
Fed by earlier layers
- L10:1880 excites
- L10:2607 weakly excites
- L9:2498 weakly excites
- L14:464 weakly excites
- L1:2338 weakly excites
- L7:2204 weakly suppresses
- L7:1951 weakly suppresses
- L10:905 weakly excites
- L12:1969 weakly excites
- L3:1533 weakly excites
- L5:664 weakly excites
- L13:2710 weakly excites
- L2:2059 weakly suppresses
- L14:637 weakly excites
- L12:2204 weakly suppresses
- L8:2426 weakly excites
- L2:2482 weakly excites
- L8:1555 weakly suppresses
- L10:2913 weakly excites
- L5:2037 weakly excites
- L12:1265 weakly suppresses
- L5:901 weakly suppresses
- L12:218 weakly excites
- L9:1994 weakly excites unclear: sun angles, geometry and road-safety terms
Feeds later layers
- L19:154 excites
- L18:623 weakly excites
- L16:956 weakly excites
- L20:384 weakly suppresses
- L19:2035 weakly suppresses
- L16:1139 weakly excites 'and' in lists of places or names
- L16:2639 weakly excites
- L16:2459 weakly excites
- L18:2949 weakly excites
- L18:2364 weakly suppresses
- L17:2237 weakly suppresses
- L24:183 weakly excites
- L27:1145 weakly excites
- L16:1720 weakly suppresses
- L18:1890 weakly suppresses
- L16:861 weakly excites
- L26:1252 weakly suppresses
- L18:1726 weakly excites
- L26:1527 weakly excites
- L25:1344 weakly excites
- L21:816 weakly suppresses
- L18:2833 weakly suppresses
- L20:529 weakly excites
- L19:3022 weakly suppresses
Activation histogramA chart of how often a neuron takes each activation value.
How often this neuron fires at each strength. Almost always it does close to nothing (the tall bars in the middle); the snippets above are the rare moments it fired hard, amber for positive and blue for negative.
Logit lensReading which output tokens a neuron pushes toward or away from, straight off its output weights, before the later layers have their say.
The words this neuron nudges the model toward (amber) or away from (blue) when it fires. A hint, not a label: many neurons work through later layersOne step in the stack the text passes through. Qwen3-0.6B has 28 layers, each with 3,072 neurons. instead.
Promotes
- vvm
- essional
- 新时代
- tern
- _API
- entai
- 全新的
- sexy
- очек
- 民国
Suppresses
- 忙
- 尽力
- 彼
- '
- 彷
- IAN
- ضة
- Guar
- 后
- 祝