Neuron Explorer

Qwen3-0.6B

'of' inside institution names

A neuron in layer 11 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 fires on the word 'of' inside the names of learned societies and academies, such as 'Royal Society of' and 'National Academy of'. It turns negative on words in app store names like 'App Store' and on 'deep web'. Turning it up gave text that did not match this theme.

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 activation was highest. Amber marks positive activation; the outlined token is the peak. Hover a token for its strength.

  1. #1 peak

    that is debt⏎Tc = corporate tax rate<|endoftext|>by Antony Williams PhD, Vice President of Strategic Development, Royal Society of Chemistry⏎When doodling in a planning meeting last year Professor Graham Richards of Oxford

  2. #2 peak

    ⏎19.01.2017 | CeMM Forschungszentrum für Molekulare Medizin der Österreichischen Akademie der Wissenschaften⏎An important step towards a completely new experimental access to quantum

  3. #3 peak

    ontë's “Jane Eyre” — is considered an integral part of the literary canon, but what makes her so great?⏎In celebration of the Royal Society of Literature’s 200th birthday, and the 10th anniversary

  4. #4 peak

    parent” coal mining company.⏎The new corporation was to transact its business in Heilwood, Indiana County, Pennsylvania, but its initial stockholders and board of directors were once again (as with the Heilwood Coal Company) all from

  5. #5 peak

    8:15)⏎Paroh’s magicians could not duplicate the plague of Lice. They told Paroh that this plague was the “finger of the L-rd”. Rashi seems to indicate that the magicians were attesting

  6. #6 peak

    he was very influenced by romantic artists like Fuseli and Blake, as well as by his continued friendship with Coleridge. He was accepted to the Royal Academy of Art and did portrait and historical paintings. When in London he nearly finished a painting

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: --- *blank --- --- --- not

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

    2009.⏎Entirely unregulated and decentralized, Bitcoin found popularity with deep web users who prized it for the pseudo-anonymity and ease of transfer. Before

  2. #2 peak

    cutest and silliest content that we could devise."⏎Cat Spanish is now available to download in the iTunes App Store for 99 cents. More languages are expected, but CatAcademy

  3. #3 peak

    and it won’t be so confusing. Instead of purchasing an app on a disk at the physical location of a store, you download them from the Windows 8 Store directly to your computer.⏎Check out this article from our archives to learn more about

  4. #4 peak

    |⏎Amazon Web Services (AWS) is a collection of remote computing services (also called web services) that together make up a cloud computing platform, offered over the Internet by Amazon.com. The most central and well-known of these services are Amazon EC

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. L6:768 strongly excites
  2. L1:1508 strongly suppresses
  3. L6:719 excites
  4. L1:1390 excites
  5. L1:2988 excites
  6. L3:2042 excites
  7. L6:643 suppresses
  8. L10:1865 suppresses
  9. L5:1238 suppresses
  10. L0:1678 excites
  11. L5:2416 excites
  12. L10:1069 excites
  13. L7:1354 excites
  14. L5:2509 suppresses
  15. L10:803 excites
  16. L5:2900 suppresses
  17. L6:1528 excites
  18. L5:1136 suppresses
  19. L7:1540 weakly suppresses
  20. L10:1160 weakly suppresses
  21. L9:2580 weakly suppresses
  22. L4:1335 weakly excites
  23. L10:1498 weakly suppresses
  24. L9:2850 weakly suppresses

Feeds later layers

  1. L12:2033 strongly suppresses
  2. L16:2799 strongly excites
  3. L18:898 strongly suppresses
  4. L13:1698 excites
  5. L17:894 suppresses
  6. L14:1929 suppresses
  7. L15:1967 excites
  8. L17:1610 excites
  9. L18:2866 excites
  10. L15:3031 suppresses
  11. L14:935 suppresses
  12. L17:1120 excites
  13. L18:1782 suppresses
  14. L20:627 suppresses
  15. L18:814 suppresses
  16. L16:1635 suppresses
  17. L12:2554 suppresses
  18. L16:1460 suppresses 'of' after a group noun
  19. L13:1234 excites
  20. L12:571 excites
  21. L14:3038 suppresses 'the' after across, around or of
  22. L18:2530 weakly excites
  23. L17:1157 weakly suppresses
  24. L19:2340 weakly suppresses

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 -9.82 and -9.441 values between -6.04 and -5.661 values between -5.66 and -5.291 values between -5.29 and -4.913 values between -4.91 and -4.531 values between -4.53 and -4.152 values between -4.15 and -3.776 values between -3.77 and -3.404 values between -3.40 and -3.029 values between -3.02 and -2.645 values between -2.64 and -2.2614 values between -2.26 and -1.8828 values between -1.88 and -1.5128 values between -1.51 and -1.1365 values between -1.13 and -0.75134 values between -0.75 and -0.37691 values between -0.37 and 0.012324 values between 0.01 and 0.38565 values between 0.38 and 0.7621 values between 0.76 and 1.141 values between 2.65 and 3.031 values between 3.03 and 3.411 values between 3.41 and 3.791 values between 4.92 and 5.30offnegativepositiveoften

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. lessness
  2. uo
  3. ところ
  4. fulness
  5. 埒
  6. 仅次于
  7. Enough
  8. arisen
  9. enton
  10. 溲

Suppresses

  1. esz
  2. krit
  3. cott
  4. 瑟
  5. änger
  6. 各
  7. ctl
  8. gaard
  9. 每人
  10. ']:⏎