'the' after 'to' in fixed 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. 18 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 responds to the word "the" when it comes right after "to", as in "to the point of", "to the west" or "burned to the ground". It is pushed the other way by some abbreviations and spelled-out terms. Turning it up made the text repeat "the" a lot without a clear meaning.
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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(and ‘living’) foods, well, alive! In a world inundated by highly processed or Genetically Modified foods that use chemicals as preservatives, to the point where animals will not even consider what we eat to be edible (see note
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on paper. Never mind what words they actually wrote, whether they used printing or cursive is Everything.⏎It's pretty serious business in Japan as well, to the point where a Japanese teacher, without seeing the actual action of writing taking place,
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005, over 7,000 natural disasters worldwide had taken the lives of nearly 2 million people and produced economic losses of more than $1
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The two rims are separated by a distance of only a couple of kilometers. To the west is the bowl-shaped crater Schmidt, and farther to the north are Manners
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. history. The attack on the Greenwood section of Tulsa, home to a prosperous African American community in the segregated city, left over 35 blocks burned to the ground and over 10,000 people — most of them black
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discussion of issues of race in the 1960s through the use of science fiction is an excellent example of this sort of approach. Now, to the matter of policebots.⏎The policebots under consideration are
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 need to *over* the * ** ** the * *** *** **** *** *** over the *** **** ***** need to ********** over the *****
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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in nearly every single manufacturing sector.⏎The possibilities of including women in this field are limitless. More women are pursuing college degrees in the fields of STEM (Science, Technology, Engineering, and Math) than ever before. Common misconceptions
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D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | 0-
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amount of tolerable global emissions over a period of time -- has to be set roughly at 1,600 Gt CO2 eq (gigatonnes of carbon dioxide equivalent) between 1990 and 20
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ters, ditches, man-made channels, storm drains, etc.) that is also:⏎- Owned or operated by a public entity (which can include cities, townships, counties, military bases, hospitals, prison complexes,
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
- L10:445 strongly excites
- L2:1585 strongly excites
- L7:219 strongly excites
- L0:246 strongly excites
- L4:613 strongly excites
- L17:166 strongly excites
- L16:205 strongly suppresses
- L1:30 strongly suppresses
- L16:827 strongly suppresses
- L0:495 strongly excites
- L17:360 strongly suppresses
- L16:260 excites
- L10:393 suppresses signs and constants in equations
- L7:674 suppresses
- L2:2029 suppresses
- L17:509 suppresses
- L0:2471 suppresses
- L17:420 excites
- L2:292 excites
- L16:353 excites
- L16:524 excites
- L13:620 excites
- L6:1434 excites
- L10:951 suppresses
Feeds later layers
- L20:164 strongly suppresses
- L19:643 strongly suppresses
- L22:2254 strongly suppresses
- L21:1112 suppresses
- L19:1865 excites
- L27:1887 suppresses
- L27:2672 suppresses word-start 't' fragment in split words
- L19:526 excites
- L26:1501 suppresses
- L26:1899 suppresses
- L26:2433 suppresses
- L21:2676 suppresses
- L19:1878 excites
- L23:918 suppresses
- L23:2868 suppresses
- L26:2921 suppresses
- L25:2552 excites
- L23:2818 suppresses
- L19:563 excites
- L25:2836 suppresses
- L20:359 excites
- L27:2092 suppresses
- L21:1793 excites
- L26:1224 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
- IDER
- IME
- agu
- berger
- ihar
- icense
- FTER
- keley
- iders
- иде
Suppresses
- perature
- vj
- ож
- sort
- ология
- .operations
- kindly
- verse
- sort
- ór