"be" after modal verbs
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. 23 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 "be" when it follows a helper word like "may", "will" or "would". Turning it down made the model repeat "not only not", so it seems tied to the negation words it can hold back.
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.
-
main point; and evidence substantiation.⏎You will need to understand the sentence’s intention and keep an eye out for brevity and succinctness.⏎You will be quizzed on all the usual suspects: commas, semicolons and col
-
your children appropriate bathroom habits or want to know whether he or she may be hitting puberty too early? If you are a parent with an uncomfortable question, you might be worried about broaching sensitive topics for fear of being judged or embarrassed. Don’t
-
adult teeth and can prevent complications and the need for more orthodontic therapy. Removable computer-generated appliances can treat selective cases in which orthodontics would otherwise be needed, but these appliances also may cost more. Removable appliances that use wires
-
including any advertising you do for your business.⏎You may be proud to tell anyone who asks that you’ve processed $50,00
-
devalue the perspectives, opinions and contributions of other team members. However, while individuals with a high subjective sense of power tend to dominate team discussions, they may be able to do so only if other team members permit it. Most likely, team
-
inske2 IMAGE OF SCIENTIST)⏎Day2PMSchinske2 IMAGE OF SCIENTIST⏎In addressing this, however, faculty members may be reluctant to engage in frank discussions about race, gender, and identity with their students
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: not only not not only not only not not not not not not not not not not not not not not not not not not not not not not not not not not not not not not not not not not not not not not not not not
Most negative on
Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.
-
times in our history where the U.S. was just not the country it was supposed to be.⏎In that sense, the story of how our nation has come to be is a story of cultural achievement, and we owe that to the people who
-
result, however, is<|endoftext|>The Getty Museum challenged people worldwide to recreate famous works of art using items from home.⏎Once again, Leah made my dream come to my life. Her chameleonic beauty makes it so easy to transform in
-
then update the positions and velocities for the next round of calculations. This scheme of computation is known as the n-body method. Perhaps Newton himself could have put it to work if
-
that has been hiding at the bottom of a lake ever since it rode to earth in a meteorite, validating the Panspermia theory of how life came to this planet?⏎Or does it lend credence to the idea that life could spring
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
- L17:2050 excites the word 'be' after modals
- L19:1001 excites "be" after will or you'll
- L16:90 suppresses
- L20:111 suppresses
- L0:110 excites
- L16:61 excites
- L3:459 suppresses
- L16:15 excites
- L20:2633 suppresses
- L18:1048 suppresses
- L17:241 weakly excites
- L20:2437 weakly excites
- L16:97 weakly excites
- L22:607 weakly excites
- L16:160 weakly excites
- L7:2851 weakly excites
- L19:2033 weakly excites
- L1:2565 weakly excites
- L19:262 weakly excites
- L4:336 weakly excites
- L20:1081 weakly excites
- L1:1210 weakly excites
- L18:102 weakly suppresses
- L16:67 weakly suppresses
Feeds later layers
- L27:714 strongly suppresses
- L26:1233 strongly suppresses
- L27:644 suppresses
- L25:802 suppresses
- L24:1811 suppresses
- L26:1452 suppresses
- L24:298 suppresses 'would' in hypothetical or past statements
- L27:796 suppresses
- L27:1006 weakly suppresses
- L24:334 weakly suppresses
- L25:472 weakly excites
- L27:1163 weakly suppresses
- L27:655 weakly suppresses
- L24:1080 weakly excites
- L24:277 weakly excites
- L25:1672 weakly suppresses
- L24:1343 weakly suppresses
- L27:932 weakly suppresses
- L27:1620 weakly suppresses
- L24:864 weakly suppresses 'to' before an infinitive
- L25:2151 weakly suppresses
- L24:787 weakly suppresses
- L24:2093 weakly excites
- L24:1696 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
- 求め
- 持ち
- erg
- embourg
- anger
- atters
- 作り
- 考え
- ULA
- runApp
Suppresses
- not
- not
- →not
- NOT
- _not
- Not
- Not
- .not
- (not
- NOT