"to" after "proved" or "proves"
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. 7 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
The neuron fires on the word "to" right after "proved" or "proves", as in "proved to be". It is one of the most consistent patterns here. Turning it up or down did not make the model write anything about proving things, so the steering gave no clear sign.
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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Wiliam’s falling off with his wealthy maternal uncles and going to his elder brother Edward to become a tradesman like him. Edward, however, proves to be a cynical and tyrant master and Wiliam is soon obliged to leave
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hold it by hand all based on what part of the room one would like to listen to and get the acoustic image from. The 40 cm camera proved to be very handy in a measurement situation where it was not given beforehand exactly where the
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do things they enjoy,<|endoftext|>86 is conjectured to be the largest power of 2 not containing a zero. This simply stated conjecture has proven itself to be proof-resistant. Let us see why.⏎What is the probability that the nth
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low, it was very difficult to detect any real change in sound pressure level from different measurement positions. Also trying to locate the origin by hearing in different positions proved to be futile when trying to determine source position. In addition to hearing the noise in
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end of the war.⏎Before World War I⏎Even before World War I⏎, the German military was already looking forward to replacing the heavy machine guns which proved to be such a success in that war. The MG13⏎was one of
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“inside” lots were sold as high as $1000.00. Within four months, these men<|endoftext|>Our discourse by now may have proved to the reader that the⏎British Empire is not as mythical as the propaganda would have
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 to do with the following: "The following is a description of the following: This is a detailed description of the following: The following is a question for the student to answer: [The following] and [the following] 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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2012 June 23⏎Explanation: As seen from Frösön island in northern Sweden the Sun did set a day
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m2 = 10-19barn). It is estimated neutrino cross-section for interaction increases linearly with energy of incident neutrino.⏎Reference: Griffiths, David, Introduction to Elementary Particles, Wiley, 19
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questions you need to know. I have her whole file and know her well.” As the conversation progresses,
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er.2008 May 27⏎Credit: Phoenix, HiRISE, NASA, JPL-Caltech, Univ. Arizona⏎Explanation: The Phoenix lander's footpads are about the size of a dinner plate
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
- L5:2603 weakly excites
- L1:1295 weakly suppresses
- L6:1840 weakly excites
- L6:867 weakly suppresses
- L6:2552 weakly suppresses
- L5:2324 weakly excites
- L6:2387 weakly excites
- L1:1109 weakly suppresses
- L6:431 weakly excites
- L1:2116 weakly suppresses
- L4:2590 weakly excites
- L3:1918 weakly suppresses
- L5:1638 weakly suppresses
- L2:2771 weakly suppresses
- L4:2283 weakly suppresses
- L5:1900 weakly excites
- L6:762 weakly excites
- L4:1248 weakly suppresses
- L1:152 weakly suppresses
- L5:2598 weakly suppresses
- L5:2179 weakly excites "the" after "one of"
- L5:956 weakly suppresses
- L6:2856 weakly suppresses
- L6:564 weakly excites
Feeds later layers
- L8:403 excites
- L15:1982 weakly excites end-of-text token and answer-stating phrases
- L8:355 weakly suppresses
- L15:400 weakly excites
- L8:2730 weakly suppresses
- L17:1863 weakly suppresses
- L25:489 weakly excites
- L19:1938 weakly excites
- L27:1352 weakly excites
- L10:2793 weakly excites
- L12:2362 weakly suppresses
- L16:1057 weakly excites
- L16:1712 weakly suppresses
- L9:2008 weakly suppresses
- L8:2514 weakly excites
- L17:2408 weakly suppresses
- L15:1588 weakly excites
- L11:2727 weakly excites
- L22:1970 weakly suppresses
- L14:752 weakly excites
- L13:1366 weakly excites
- L8:934 weakly suppresses
- L13:348 weakly excites
- L10:282 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
- rost
- ços
- agements
- (play
- AVOR
- orage
- Result
- unfavorable
- phiên
- 说是
Suppresses
- ativity
- asia
- arse
- wording
- ABCDE
- ensi
- asin
- 万户
- 发言人
- apixel