comma after a 'said' or 'answered' verb
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. 6 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 fires on the comma or colon right after a speech verb like "answered", "asked" or "yelled", just before a quotation starts. Turning it up did not produce a clear change in the stories.
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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Upon seeing the many dinosaurs displayed in the museum, the boys asked if evolutionists are right saying the dinosaurs lived tens of millions of years ago.⏎Lisle answered, "They like to believe that dinosaurs are millions of years old and that the earth
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Stephanie looks up and nods but does not say anything. Dr. Smith introduces herself to Stephanie’s caseworker, Hannah, then turns back to Stephanie and asks, “Tell me how you have been doing over the past year, Stephanie.”⏎Step
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to meet. The women carried signs that read, "Down with the National Conference without women!", "Stop Injustice!", and "Equal Rights!" They also shouted, "Away with the National Conference without Women!"⏎Alio resigned from the Pre
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evolved from a banana, does it?"⏎Ryan started to wonder about how the universe began, asking Lisle, "What about the Big Bang?"⏎Lisle answered, "The Big Bang teaches<|endoftext|>Fig.1 above refer to a point moving along
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in later.⏎It took fifteen minutes to complete the scene. When it was over, DeMille yelled, “Cut!” and turned to his assistant, all smiles. “That was great
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dens, and birds of the sky have nests, but the Son of Man has no place to lay His head.”⏎New American Standard BibleAnd Jesus said to him, "The foxes have holes and the birds of the air [have] nests
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: The best way to start is to make a great deal of. If I had to choose the best time to make it. Maybe a great deal of is a place to start." I like to think that I have been thinking about lately.
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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if you just ask “Is your person [name]?”.⏎Players are quick to understand that by asking questions that divide the candidates into two groups, such as “is your person female?”, you can reduce the candidate pool more quickly.⏎If
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always train new users on how to use these tools.⏎But searching tools alone are usually not enough. For example, a user might search for a term such as "Individual"⏎not knowing that you stored information about human beings under the class "Person
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about how it is going to work, he is uncertain about it. When he is pretty sure of how it is going to work, and he tells you, "This is the way it's going to work, I'll bet," he still
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link="none" columns="2" size="medium" ids="2568,256
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
- L2:1824 weakly suppresses
- L1:132 weakly excites
- L5:2364 weakly suppresses
- L1:1538 weakly suppresses
- L4:2866 weakly suppresses the word 'average' before a quantity
- L4:218 weakly excites
- L5:2145 weakly suppresses
- L4:25 weakly excites
- L4:1824 weakly suppresses
- L2:209 weakly suppresses 'also' after 'not only ... but'
- L1:1366 weakly excites
- L5:404 weakly suppresses
- L2:1418 weakly excites
- L5:272 weakly suppresses
- L4:51 weakly suppresses
- L4:507 weakly suppresses
- L0:134 weakly suppresses
- L2:2662 weakly suppresses
- L2:193 weakly excites
- L4:1243 weakly suppresses
- L4:2495 weakly suppresses
- L5:2231 weakly excites
- L3:2652 weakly suppresses
- L1:2425 weakly excites
Feeds later layers
- L9:316 suppresses
- L10:1339 excites
- L10:778 suppresses
- L16:455 suppresses
- L15:1515 excites
- L7:256 suppresses
- L9:299 suppresses
- L18:478 suppresses
- L21:2669 weakly suppresses
- L11:966 weakly excites
- L24:2884 weakly suppresses
- L15:277 weakly suppresses
- L8:21 weakly excites
- L14:830 weakly suppresses
- L27:1748 weakly excites
- L11:769 weakly suppresses
- L12:2582 weakly suppresses
- L7:207 weakly excites
- L7:1031 weakly excites
- L11:1228 weakly excites
- L14:1111 weakly suppresses
- L12:8 weakly excites
- L15:1853 weakly suppresses
- L14:3053 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
- сп
- ска
- قة
- Killer
- erged
- 阔
- ctor
- 肆
- sobre
- Dec
Suppresses
- afari
- 金字
- dział
- 您的
- 您的孩子
- sist
- columnName
- ABCDEFGHIJKLMNOPQRSTUVWXYZ
- ptom
- 癖