Neuron Explorer

Qwen3-0.6B

unclear: word before a noun in lists

A neuron in layer 14 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

It fires on a scattered mix of words, often the word just before a noun in a list or a formal phrase, such as 'both' or 'two'. The pattern is loose and hard to pin down. Turning it up made the model drift into questions or repeat itself.

Written by Claude from this neuron's activations and steering outputs. Confidence: low. 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

    ulopathy, and the acute coagulopathy of trauma-shock (ACoTS) [2,3,5,6].⏎The etiology, diagnosis and treatment of coagul

  2. #2 peak

    and underscored the critical need for effective cooperation on border biosecurity measures.⏎Biosecurity is critical to protecting public health, ecosystems and a country’s economy. As countries become increasingly interconnected through global trade, travel and movement of

  3. #3 peak

    and group practice. Instructors also administer quizzes and full-length practice sections of the SAT. This allows instructors to identify areas in which students need improvement and provides both instructors and students with . If students do not improve their scores it is because either did

  4. #4 peak

    illustration of how one subject is put for another is found in comparing the two seemingly contradictory biblical accounts of the death of King Saul. Remember that in the Old

  5. #5 peak

    production assistant. Each of these positions are defined along with their respective duties, rules, and resources that figure in obtaining these jobs. Each chapter offers exercises, links

  6. #6 peak

    required materials, discussion of course policies, an overview of class assignments, and grading standards. Updated:

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 2015, 2017, 2018, 2019, 2010, 2010, 2019, 20

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

    label at least 85% of that wine must come from within that AVA boundary. The AVA designation on a wine label usually appears just above the grape varietal description. The AVA designation does not limit the types of grapes

  2. #2 peak

    and the goals; and evaluations of the process itself and of the implementation and results of the action plan, with an eye toward improving MAPP’s effectiveness in the community as it’s

  3. #3 peak

    two days after the hot weather. Night-time cooling can help reduce the negative effects of heat load on production, but it does not reduce the welfare impact on the cows during the day.⏎In the summer of 2021 the Waik

  4. #4 peak

    five hours of instruction per week. Secondary school students who qualify for homebound instruction are eligible to receive a maximum of ten hours of instruction per week depending on their academic load. If appropriate to the needs of the child, the number of instructional hours

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. L13:2134 suppresses
  2. L13:367 excites
  3. L13:1432 excites
  4. L11:475 excites
  5. L11:1391 suppresses
  6. L11:1974 excites
  7. L13:1541 suppresses
  8. L12:2060 excites
  9. L13:1198 excites
  10. L8:594 excites
  11. L12:1275 excites
  12. L12:2201 suppresses
  13. L13:2755 weakly suppresses
  14. L11:598 weakly suppresses
  15. L13:2415 weakly suppresses
  16. L10:1885 weakly excites
  17. L13:2768 weakly suppresses
  18. L7:2428 weakly excites
  19. L12:2000 weakly suppresses
  20. L12:1685 weakly excites
  21. L12:204 weakly suppresses
  22. L12:1421 weakly excites
  23. L7:33 weakly excites
  24. L12:2607 weakly suppresses

Feeds later layers

  1. L15:974 excites
  2. L16:1307 suppresses
  3. L15:509 suppresses
  4. L15:412 excites
  5. L15:1592 excites
  6. L16:2183 excites
  7. L15:1661 suppresses
  8. L15:3051 excites
  9. L15:132 excites
  10. L17:1796 suppresses
  11. L15:2000 weakly suppresses
  12. L15:2593 weakly suppresses
  13. L17:2975 weakly suppresses
  14. L19:837 weakly excites
  15. L15:2190 weakly excites
  16. L15:2019 weakly suppresses
  17. L17:2529 weakly suppresses
  18. L16:1357 weakly excites
  19. L15:414 weakly suppresses
  20. L15:794 weakly suppresses
  21. L15:534 weakly excites
  22. L15:273 weakly excites
  23. L19:673 weakly excites
  24. L23:2001 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.

2 values between -2.43 and -2.291 values between -1.63 and -1.503 values between -1.37 and -1.248 values between -1.24 and -1.105 values between -1.10 and -0.9712 values between -0.97 and -0.8413 values between -0.84 and -0.7130 values between -0.71 and -0.5757 values between -0.57 and -0.4476 values between -0.44 and -0.31206 values between -0.31 and -0.18640 values between -0.18 and -0.051799 values between -0.05 and 0.09597 values between 0.09 and 0.22219 values between 0.22 and 0.35102 values between 0.35 and 0.4853 values between 0.48 and 0.6226 values between 0.62 and 0.7520 values between 0.75 and 0.8814 values between 0.88 and 1.017 values between 1.01 and 1.155 values between 1.15 and 1.284 values between 1.28 and 1.414 values between 1.41 and 1.541 values between 1.68 and 1.812 values between 1.81 and 1.941 values between 1.94 and 2.071 values between 2.73 and 2.87offnegativepositiveoften

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. ques
  2. thalm
  3. _Base
  4. _macros
  5. vergence
  6. 耽误
  7. foundation
  8. imating
  9. _Task
  10. _FILL

Suppresses

  1. loom
  2. ":"'
  3. 并
  4. cop
  5. 并向
  6. ]+'
  7. emu
  8. eced
  9. 並
  10. clue