"the" after time or place prepositions
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. 20 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" when it follows a preposition such as "at", "from", or "over" in phrases like "at the same time", "from the perspective of" or "over the past decades". Its activations are weak compared with the other neurons here. Turning it down made the model output "the the the" repeatedly, so the outputs do not show the trigger clearly.
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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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 the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the 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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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
- L19:2283 strongly suppresses
- L18:861 strongly suppresses
- L19:1023 strongly excites
- L19:644 strongly excites
- L19:1180 strongly suppresses
- L18:1359 excites
- L11:223 excites
- L16:1320 suppresses
- L11:1168 excites
- L13:44 suppresses inside web addresses and citations
- L10:155 excites
- L17:30 suppresses
- L15:184 excites
- L18:1041 suppresses
- L18:178 excites
- L18:1909 suppresses
- L7:92 excites
- L18:1513 suppresses
- L17:372 suppresses
- L3:344 excites
- L10:1644 excites
- L17:1056 excites
- L12:158 suppresses
- L18:635 excites
Feeds later layers
- L24:153 strongly suppresses
- L21:614 strongly excites
- L21:592 excites
- L25:390 excites
- L21:675 suppresses
- L25:544 suppresses
- L24:327 excites
- L25:284 suppresses
- L23:79 suppresses
- L21:310 suppresses
- L27:193 suppresses
- L21:547 excites
- L24:261 suppresses
- L26:1941 excites
- L24:918 suppresses
- L21:2342 suppresses
- L27:173 excites
- L27:421 excites
- L22:171 suppresses
- L27:797 suppresses
- L23:392 suppresses
- L27:663 suppresses
- L22:2302 suppresses
- L26:213 excites
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
- 好的
- own
- same
- 该
- 該
- 自己
- same
- oretical
- Crow
- 平
Suppresses
- кра
- EndInit
- очно
- ıy
- téc
- lijk
- (errno
- ело
- سوء
- ела