Neuron Explorer

Qwen3-0.6B

the modal 'can' after 'there' or 'it'

A neuron in layer 24 of Qwen3-0.6B. Its strongest snippets are very consistent: they mostly peak on the same token. It is featured, so it has steering outputs.

What this neuron does

This neuron lights up on the word "can" when it means "is possible", especially in phrases like "there can be" or "it can be". When it was turned up, the model got stuck repeating "can't be able to", so this neuron seems tied to talking about what is possible.

Written by Claude from this neuron's activations and steering outputs. Confidence: high. Think it is wrong? Flag it (opens a prefilled issue on GitHub).

Fires most on

The text windows where this neuron's activation was highest. Amber marks positive activation; the outlined token is the peak. Hover a token for its strength.

  1. #1 peak

    be done when the beetle is dormant to prevent further spreading, Eddy says. She adds, "There is no one textbook way of dealing with this because there can be so many different circumstances."⏎For now, the city wants to educate residents about

  2. #2 peak

    had access to more general care, the physical body second. This has all changed in the past few years.⏎Mental health professionals and organizations now know that there can't be a separation between a brain and body when it comes to effective psychiatric treatment

  3. #3 peak

    ose rich foods. For these people there can be many negative side effects to ingesting dairy products that include but are not limited

  4. #4 peak

    the various agencies are getting closer and closer to finding aliens, while at the same time, we have almost no idea about how powerful the military technologies of the aliens can be and whether they will be friendly to the human or not; I start to

  5. #5 peak

    Icon (1954). They correctly criticized the belief that the intention of the author was the one and only correct interpretation of a work. Certainly, there can be other valid interpretations of a work, and of course the literature scholar should not

  6. #6 peak

    know how difficult it can be to get into a story and then keep readers engaged while they wait for the

Steering

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.

turned down a lot
Prompt

Here is something I have been thinking about lately: the first instance in the context of the sushput is sushput is the first part of the sushput sushput sushput sushput sushpush. sushpush is the sushpush sushpush

Most negative on

Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.

  1. #1 peak

    -ethnic neighbourhoods in England, by Dr Gemma Catney, Professor Richard Wright, and Professor Mark Ellis. The original article, posted in Geography Directions, can be accessed here. You can also read the full article published in Transactions of the

  2. #2 peak

    that he would eliminate most U. S. cabinet departments, including those overseeing commerce, education, energy, and labor (some of this material and references for it can be found in my An Age

  3. #3 peak

    You can see where it is in the solar system on the JPL Small Body Database Browser. Here is the map for today:⏎As you can see in the map, it's a main belt asteroid, orbiting the Sun

  4. #4 peak

    a sentence that is split over several lines in HTML. </BODY> </HTML>When this is displayed by Mosaic, it will look like:⏎As you can probably guess, commands are enclosed in angle-brackets <>, so that the HTML

Connections

Show on map

Which neurons in earlier layers feed this one, and which later ones it feeds. Amber links excite, blue links suppress; longer bars are stronger.

Fed by earlier layers

  1. L17:953 strongly excites the word 'can' after a subject
  2. L19:1473 excites "can" after a noun in a clause
  3. L4:173 suppresses
  4. L10:384 excites
  5. L21:2007 suppresses
  6. L3:978 suppresses
  7. L19:2701 suppresses
  8. L18:1491 suppresses
  9. L15:886 excites
  10. L20:2097 suppresses
  11. L10:2166 excites
  12. L23:30 suppresses
  13. L21:262 excites
  14. L0:1372 weakly suppresses
  15. L20:636 weakly suppresses
  16. L5:387 weakly excites
  17. L11:360 weakly suppresses
  18. L19:545 weakly excites
  19. L13:2339 weakly excites
  20. L10:562 weakly excites
  21. L16:127 weakly suppresses
  22. L5:1203 weakly suppresses
  23. L20:1897 weakly suppresses
  24. L18:2634 weakly excites

Feeds later layers

  1. L27:774 strongly excites
  2. L27:2857 excites
  3. L27:1802 excites
  4. L27:1815 weakly excites
  5. L25:2101 weakly excites
  6. L25:1821 weakly excites
  7. L25:752 weakly excites
  8. L25:757 weakly excites
  9. L26:1853 weakly excites
  10. L26:1370 weakly suppresses
  11. L27:388 weakly excites
  12. L27:1021 weakly excites
  13. L26:1645 weakly suppresses
  14. L27:2079 weakly excites
  15. L25:2021 weakly suppresses
  16. L27:2103 weakly excites
  17. L27:1011 weakly suppresses
  18. L27:955 weakly excites
  19. L27:1464 weakly excites
  20. L25:1617 weakly excites
  21. L27:2230 weakly excites
  22. L26:218 weakly suppresses
  23. L27:2314 weakly suppresses the letter l starting a word fragment
  24. L26:2655 weakly excites

Activation histogram

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.

1 values between -8.48 and -7.371 values between -7.37 and -6.251 values between -5.14 and -4.035 values between -4.03 and -2.925 values between -2.92 and -1.8190 values between -1.81 and -0.703549 values between -0.70 and 0.41173 values between 0.41 and 1.5227 values between 1.52 and 2.6418 values between 2.64 and 3.756 values between 3.75 and 4.864 values between 4.86 and 5.975 values between 5.97 and 7.088 values between 7.08 and 8.194 values between 8.19 and 9.303 values between 9.30 and 10.411 values between 11.52 and 12.641 values between 14.86 and 15.972 values between 19.30 and 20.411 values between 22.64 and 23.751 values between 27.08 and 28.191 values between 29.30 and 30.411 values between 34.86 and 35.97offnegativepositiveoften

Logit lens

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 layers instead.

Promotes

  1. 能
  2. can
  3. 可以
  4. can
  5. 可
  6. 能够
  7. 能夠
  8. Can
  9. 能在
  10. →can

Suppresses

  1. reta
  2. WORDS
  3. 둥
  4. unched
  5. credentials
  6. выполнен
  7. 酋
  8. chimp
  9. 闻
  10. htags