Neuron Explorer

Qwen3-0.6B

person names and role nouns

A neuron in layer 15 of Qwen3-0.6B. Its strongest snippets are mixed: they peak on different tokens. It is featured, so it has steering outputs.

What this neuron does

This neuron responds to words that name a person or a role, like 'queen', 'manager', 'mother', a person's name, or a company's leader. When it was turned up, the model drifted toward talking about people and their situations.

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

    about the universe is wrong. Physicist and best-selling author Brian Greene takes you on a journey that bends the rules of human experience.⏎BRIAN GREENE (Columbia University): Why don't we ever see events unfold

  2. #2 peak

    Dr. Nuha El Sayed, vice president of Healthcare Improvement at the American Diabetes Association. Hi, thanks for joining me.⏎Dr. Nuha El Sayed: Thank you for having me.⏎So, today I would love to pick your

  3. #3 peak

    2008 Express Edition >> Visual Studio Tools >> Visual Studio 2008 Command Prompt (Run with administrator privileges)⏎- Once you are in the command line, you can use any editor such as edit to write a C program.⏎

  4. #4 peak

    reaction to this paragraph?⏎The king neglected his wife?⏎He drank too much?⏎The Queen was busy with her own guests?⏎Put yourself in the place of the queen if you are female, the place of the king if you are male. How

  5. #5 peak

    synopsis of the first video in the series written by a guest on this blog, Roni Jacobson, a science journalist based in New York City.⏎By Roni Jacobson⏎Being unable to recall a word on

  6. #6 peak

    maximising costs and power savings - a critical challenge to overcome for the success of any exascale initiative," said Vishal Dhupar, managing director of NVIDIA India.⏎The development of exascale computing systems, which would be hundreds of

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 "f" and "f" in the context of the "f" and "f" in the context of the "f" and "f" in the "f" and "f" in the "f" and "

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

    however freely search the site and view the abstracts and keywords for each book and chapter.⏎If you think you should have access to this title, please contact your librarian.⏎To troubleshoot, please check our FAQs, and if you can't find

  2. #2 peak

    of Frank Churchill’s secret engagement to Jane.⏎“Good God!” cried Emma, “Jane actually on the point of going as governess! What could he mean by such horrible indelicacy? To suffer her to engage herself — to

  3. #3 peak

    abstracts and keywords for each book and chapter.⏎If you think you should have access to this title, please contact your librarian.<|endoftext|>Information on creating school gardens for outdoor learning, compiled by the National Clear

  4. #4 peak

    is for Gertrude to try and determine what is going on with Hamlet. She starts out on the offensive, accusing him of offending his (step-) father, Claudius. Hamlet is already in high spirits having just missed an opportunity

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. L13:1448 excites
  2. L0:620 suppresses
  3. L13:1119 weakly excites
  4. L13:1680 weakly excites
  5. L13:1635 weakly excites
  6. L10:2135 weakly suppresses
  7. L12:1946 weakly suppresses
  8. L7:36 weakly suppresses
  9. L11:1264 weakly suppresses
  10. L12:2999 weakly excites
  11. L13:770 weakly excites
  12. L13:2201 weakly suppresses
  13. L14:2260 weakly excites
  14. L11:751 weakly suppresses numbers and quantities mid-phrase
  15. L13:1765 weakly suppresses
  16. L0:698 weakly excites
  17. L1:865 weakly suppresses
  18. L14:468 weakly suppresses
  19. L3:972 weakly excites
  20. L14:2618 weakly suppresses
  21. L11:1704 weakly suppresses
  22. L5:1111 weakly excites
  23. L12:710 weakly excites
  24. L5:1214 weakly suppresses

Feeds later layers

  1. L16:1182 excites
  2. L16:2819 excites
  3. L16:2803 weakly suppresses
  4. L17:1070 weakly excites
  5. L17:570 weakly excites
  6. L23:1624 weakly excites
  7. L21:1699 weakly suppresses
  8. L22:1646 weakly excites
  9. L21:3041 weakly suppresses
  10. L19:2961 weakly suppresses
  11. L18:756 weakly excites
  12. L18:3060 weakly suppresses
  13. L25:1668 weakly excites
  14. L26:820 weakly excites
  15. L23:823 weakly suppresses
  16. L25:2351 weakly suppresses
  17. L17:2098 weakly suppresses
  18. L22:2664 weakly suppresses
  19. L16:2657 weakly excites
  20. L17:1245 weakly excites
  21. L16:877 weakly suppresses
  22. L20:821 weakly suppresses
  23. L18:2086 weakly suppresses
  24. L20:161 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.

3 values between -1.83 and -1.721 values between -1.51 and -1.413 values between -1.20 and -1.092 values between -1.09 and -0.992 values between -0.99 and -0.885 values between -0.88 and -0.785 values between -0.78 and -0.676 values between -0.67 and -0.5712 values between -0.57 and -0.4629 values between -0.46 and -0.3664 values between -0.36 and -0.25204 values between -0.25 and -0.15625 values between -0.15 and -0.041597 values between -0.04 and 0.06755 values between 0.06 and 0.17334 values between 0.17 and 0.27137 values between 0.27 and 0.3854 values between 0.38 and 0.4826 values between 0.48 and 0.5910 values between 0.59 and 0.697 values between 0.69 and 0.804 values between 0.80 and 0.906 values between 0.90 and 1.016 values between 1.01 and 1.112 values between 1.11 and 1.212 values between 1.21 and 1.322 values between 1.32 and 1.421 values between 1.42 and 1.532 values between 1.63 and 1.741 values between 1.84 and 1.951 values between 2.26 and 2.37offnegativepositiveoften

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. ception
  2. cep
  3. 听着
  4. 绉
  5. ze
  6. cej
  7. pii
  8. admins
  9. 当たり
  10. acie

Suppresses

  1. amb
  2. chaft
  3. oolStrip
  4. 洲
  5. ServiceProvider
  6. iom
  7. probante
  8. =yes
  9. gren
  10. vestment