Neuron Explorer

Qwen3-0.6B

surnames in bylines and credits

A neuron in layer 11 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 fires on the letters inside a person's surname, especially in author bylines and credits like 'Angela Raven-Roberts' or 'Priscilla Stuckey-Kauffman'. When it was turned up, the model's writing got stuck in loops and drifted off topic, so it does not clearly change the meaning of the text.

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

    and Livia Visser-Fuchs:⏎“A ‘Most Benevolent Queen’: Elizabeth Woodville’s Reputation, her

  2. #2 peak

    top scholars discuss the historical Israelites in Egypt and archaeological evidence for and against the historicity of the Exodus.⏎BAR coauthor Lily Singer-Avitz suggests that several finds discovered in the later strata, including Egyptian-style

  3. #3 peak

    eating solids," Henderson said. "Both [of her children] have been pretty adventurous, both were willing to try things really early on."⏎Karen Sussman-Karten, 48, of Newton, Mass., noticed her three children nurs

  4. #4 peak

    The Big Picture? An Afterword⏎PortraitDyan Mazurana is senior research fellow at the Feinstein International Famine Center, Tufts University. Angela Raven-Roberts is director of research and programs at the Feinstein Famine Center, Tu

  5. #5 peak

    first proposed the idea for a national food security initiative.⏎"It is also about free trade without having to sacrifice a part of the economy," said Economics Minister Johann Schneider-Ammann.⏎While the expected vote

  6. #6 peak

    after a baby’s birth, a period that has been dubbed the “magic moment.” The new study is the first to test that assumption, said author Christina Gibson-Davis. “It turns out the ‘magic moment’ lasts longer than conventional wisdom

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 time, I don't know, the second time, and the second time, and the first time and the second time, and the second time, and the first time, and the second time, and the first time, 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

    body. This disease is also commonly known as Chhoti Mata. Whoever suffers from smallpox disease starts having itching and itching problems all over the body.⏎Reasons for chicken pox⏎There are many reasons for chicken pox, some

  2. #2 peak

    wells are still in use.⏎The ancient city of Hegra/Al-Hijr bears witness to the international caravan trade during late Antiquity.⏎Criterion (ii): The site of Al-Hijr is located at a meeting point between various

  3. #3 peak

    foods may trigger acne and other face conditions.⏎II. Foods to avoid if you have sensitive skin⏎Spicy foods, such as

  4. #4 peak

    person from a disadvantaged background is both more likely to experience poor health and less likely to have access to the services and the care that they may need.⏎Fact 6: Ageism may now be more pervasive than sexism or racism⏎Ageism

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. L9:2528 excites
  2. L0:2252 weakly suppresses
  3. L5:2988 weakly suppresses
  4. L5:221 weakly excites
  5. L2:1578 weakly excites
  6. L8:727 weakly excites
  7. L2:870 weakly suppresses
  8. L6:2160 weakly excites
  9. L10:1545 weakly suppresses
  10. L0:2013 weakly suppresses
  11. L7:501 weakly excites
  12. L10:634 weakly excites
  13. L5:2212 weakly suppresses
  14. L10:141 weakly suppresses
  15. L7:267 weakly suppresses
  16. L0:878 weakly suppresses 'because' after a claim
  17. L7:2064 weakly suppresses
  18. L7:1653 weakly excites
  19. L2:2422 weakly excites
  20. L7:1954 weakly excites
  21. L6:1361 weakly suppresses
  22. L3:2041 weakly excites
  23. L6:441 weakly suppresses
  24. L4:2389 weakly suppresses

Feeds later layers

  1. L12:3045 suppresses
  2. L13:2328 excites
  3. L15:2628 suppresses
  4. L12:421 excites
  5. L13:1112 suppresses
  6. L14:2169 suppresses
  7. L18:395 weakly suppresses
  8. L15:3064 weakly excites
  9. L12:1854 weakly suppresses
  10. L14:2531 weakly suppresses
  11. L19:1834 weakly suppresses
  12. L14:449 weakly excites
  13. L15:1097 weakly suppresses
  14. L16:1448 weakly suppresses
  15. L12:576 weakly suppresses 'of' in fixed phrases like table of contents
  16. L21:2694 weakly suppresses
  17. L13:700 weakly suppresses
  18. L16:498 weakly excites
  19. L13:1513 weakly suppresses
  20. L12:3030 weakly excites
  21. L23:1718 weakly excites
  22. L20:534 weakly suppresses
  23. L19:1748 weakly excites
  24. L13:1646 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 -0.56 and -0.535 values between -0.53 and -0.507 values between -0.47 and -0.446 values between -0.44 and -0.414 values between -0.41 and -0.3819 values between -0.38 and -0.3522 values between -0.35 and -0.3237 values between -0.32 and -0.2942 values between -0.29 and -0.2662 values between -0.26 and -0.2479 values between -0.24 and -0.21115 values between -0.21 and -0.18142 values between -0.18 and -0.15170 values between -0.15 and -0.12233 values between -0.12 and -0.09272 values between -0.09 and -0.06299 values between -0.06 and -0.03358 values between -0.03 and -0.00372 values between -0.00 and 0.03307 values between 0.03 and 0.06285 values between 0.06 and 0.09233 values between 0.09 and 0.12200 values between 0.12 and 0.15164 values between 0.15 and 0.18117 values between 0.18 and 0.21102 values between 0.21 and 0.2381 values between 0.23 and 0.2640 values between 0.26 and 0.2946 values between 0.29 and 0.3229 values between 0.32 and 0.3518 values between 0.35 and 0.3819 values between 0.38 and 0.4112 values between 0.41 and 0.444 values between 0.44 and 0.473 values between 0.53 and 0.561 values between 0.59 and 0.62offnegativepositiveoften

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. ardon
  2. шение
  3. праздник
  4. 器
  5. erto
  6. functionName
  7. ClassName
  8. 慑
  9. (func
  10. ards

Suppresses

  1. ennie
  2. втор
  3. toDouble
  4. ña
  5. Omn
  6. Hai
  7. 雙
  8. НЕ
  9. Documents
  10. yo