Neuron Explorer

Qwen3-0.6B

'well' in well-dressed, well-known, well-off

A neuron in layer 23 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 'well' when it appears in phrases like 'well-dressed', 'well known', 'well off' or 'well-to-do'. Turning it up made the model write comparisons and repeated phrases, which does not clearly match this word.

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

    activity. During the 1840's, this tiny village, once a mile long, was larger than Charlotte and hosted a collection of the wealthy and well-dressed. After 1849, Gold Hill lost a great deal

  2. #2 peak

    и) of the Don, Kuban, Terek and Ural rivers and the Ukrainian Cossacks (козаки), respectively. Somewhat less well known are the Polish Cossacks (Kozacy) and the Tatar

  3. #3 peak

    Savannah, Georgia after Jacob encountered financial difficulties. It is not known how much formal schooling Phoebe had, but she was clearly well read and worldly. In 1856, she married a non-J

  4. #4 peak

    .⏎This is because climate change appears to be altering the weather conditions wide-ranging birds encounter before, during + after their migration. With some species no longer being as well adapted to, or synchronised with, the conditions they encounter during their travels as

  5. #5 peak

    the foremost combat weapons.⏎Acknowledging the significance of the availability of good shields for successful warfare, Carolingian rulers took special care to ensure that their soldiers were well-supplied with ample shields.⏎Shields were used by both the cavalrymen and

  6. #6 peak

    composition.⏎The composer was born in 1810 in the village of Zelazowa Wola, not far from Warsaw. His family was not well off, but they had a strong appreciation for music. Chopin’s mother could

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: I have a new family member, a woman with a name of the same name as my mother. I have a male child with a name of the same as my father. Her name is also the same as the female name of my mother

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

    1 USA. They are now with the Department of Construction, Chaoyang University of Technology, Taichung 41349, Taiwan (corresponding author's e-mail: firstname.lastname@example.org, email@example.com).⏎Ch

  2. #2 peak

    the trends of infectious diseases and the mechanisms of Adaptive diseases.⏎Department of Pediatrics, Soroka University Medical Center, Beer-Sheva, Israel⏎- *Corresponding Author:⏎- Yeongha Wook⏎Department of Pediatrics,⏎Sor

  3. #3 peak

    Identify leaks⏎- Determine if any water fixtures or appliances are not working properly⏎- Identify irrigation system problems such as damaged or misdirected spray heads, non-functioning rain sensors or soil moisture sensors⏎- Determine how water is used at the

  4. #4 peak

    Like a whole cadre of other prosthetic researchers and makers, they are interested in breaking down the process, figuring out how to turn 3-D printing into something self-sustaining

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. L20:1976 strongly excites
  2. L20:1529 suppresses
  3. L21:916 suppresses
  4. L21:347 suppresses
  5. L20:2673 suppresses
  6. L19:1159 suppresses
  7. L21:1370 suppresses
  8. L19:2781 suppresses
  9. L18:1180 excites
  10. L22:550 suppresses
  11. L20:2831 excites
  12. L19:1739 suppresses
  13. L21:1296 excites
  14. L19:1225 excites
  15. L18:962 excites
  16. L19:2208 excites
  17. L16:1819 excites
  18. L19:561 excites
  19. L20:853 suppresses
  20. L21:1550 suppresses
  21. L21:1999 excites 'well' in compound adjectives
  22. L22:1654 suppresses
  23. L21:1872 suppresses
  24. L14:2539 weakly suppresses

Feeds later layers

  1. L24:422 strongly excites
  2. L25:349 strongly excites
  3. L27:217 excites
  4. L26:138 excites
  5. L26:144 excites
  6. L25:1852 excites
  7. L27:869 excites
  8. L27:716 excites
  9. L27:1596 excites
  10. L27:1295 excites
  11. L27:1451 excites
  12. L27:1281 excites
  13. L26:395 excites
  14. L26:1188 excites
  15. L27:1514 excites
  16. L24:258 suppresses
  17. L26:632 excites
  18. L25:644 excites
  19. L27:1832 excites
  20. L26:1940 excites
  21. L26:922 excites
  22. L26:891 excites
  23. L24:239 weakly excites
  24. L27:1110 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 -24.56 and -22.781 values between -12.09 and -10.312 values between -10.31 and -8.535 values between -6.75 and -4.9710 values between -4.97 and -3.1946 values between -3.19 and -1.413312 values between -1.41 and 0.38443 values between 0.38 and 2.1651 values between 2.16 and 3.9419 values between 3.94 and 5.726 values between 5.72 and 7.505 values between 7.50 and 9.282 values between 9.28 and 11.062 values between 11.06 and 12.841 values between 21.75 and 23.531 values between 23.53 and 25.311 values between 44.91 and 46.69offnegativepositiveoften

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. anked
  2. icked
  3. treated
  4. tested
  5. eded
  6. acted
  7. tried
  8. analyzed
  9. played
  10. initiated

Suppresses

  1. ẫn
  2. 人的
  3. になる
  4. :relative
  5. inging
  6. attaching
  7. ative
  8. 方面的
  9. ersh
  10. ewing