Neuron Explorer

Qwen3-0.6B

surname pieces split across tokens

A neuron in layer 0 of Qwen3-0.6B. Its strongest snippets are fairly consistent: several of them peak on the same token. It is featured, so it has steering outputs.

What this neuron does

The neuron fires strongly on the middle of a person's surname when the name is split into several pieces, such as 'Lo[ew]en', 'Ru[hr]' and 'Gu[ite]au'. Its strongest negative values appear on name pieces too, so it looks like a name-fragment detector with the sign depending on the case. Turning it up or down did not give a clear story in 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

    eyes and a narrow short snout, similar to its relative T. rex, which lived 10-12 million years later. Dr. Mark Loewen, the study’s lead author, noted, “The width of the back

  2. #2 peak

    Salt Lake City, Utah.⏎The study, funded in large part by the Bureau of Land Management and the National Science Foundation, was led by Dr. Mark Loewen, research associate at the Natural History Museum of Utah, and adjunct assistant professor

  3. #3 peak

    words.⏎Professor Onur Güntürkün, one of the co-investigators from of Ruhr University’s Department of Biopsychology, says “that pigeons — separated

  4. #4 peak

    can learn to distinguish real words from non-words by visually processing their letter combinations, surprising new research from the University of Otago in New Zealand and Ruhr University in Germany shows.⏎The researchers found

  5. #5 peak

    the last months of WWII) against fnatical German resistance while US forces were encircling the Ruhr and preparing to cross the⏎Now a political war began. Churchill wanted Ike to

  6. #6 peak

    easy for Charles J Guiteau to assassinate Garfield in 1881. Guiteau used a British Bull Dog revolver to shoot the President point blank in the back

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 am a young person, I have been thinking about lately, I am in my own way, I am in my own way, I am in my own way, I am in my own way, I am in my own way

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

    make<|endoftext|>Amaziah of Judah⏎Amaziah of Judah (אמציה) was a king of Judah, the son and successor of Joash, and the father of Azariah (Uzziah

  2. #2 peak

    in any rush to get there.⏎Meet future woman: shorter, plumper, more fertile [New Scientist]<|endoftext|>MERCIER, JEAN ° (Joannes Mercerus ; d. 1570), French Hebraist.

  3. #3 peak

    NC, Julio Cárcamo. However the current status of the project is unclear.⏎Main policy lessons⏎Tulio Monterroso, AMUPROLOAGO: mailto:firstname.lastname@example.org; email@example.com ;⏎Cohen,

  4. #4 peak

    with coagulopathy have a threefold to fourfold greater mortality, and are up to

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

None: this is the first layer.

Feeds later layers

  1. L10:948 excites
  2. L1:2314 weakly excites
  3. L16:631 weakly excites
  4. L2:2572 weakly excites
  5. L13:2015 weakly excites
  6. L9:1350 weakly excites
  7. L5:208 weakly suppresses
  8. L15:2104 weakly excites
  9. L7:2998 weakly suppresses
  10. L22:2266 weakly excites
  11. L19:2809 weakly excites comma after 'in this blog post'
  12. L26:1209 weakly excites
  13. L25:1634 weakly excites
  14. L16:1813 weakly suppresses
  15. L17:1562 weakly excites
  16. L19:2521 weakly excites
  17. L22:296 weakly suppresses
  18. L10:953 weakly suppresses
  19. L9:1512 weakly suppresses
  20. L8:527 weakly excites
  21. L15:2663 weakly excites
  22. L16:2044 weakly excites
  23. L22:1389 weakly suppresses
  24. L8:2802 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 -1.66 and -1.601 values between -1.60 and -1.541 values between -1.37 and -1.311 values between -0.51 and -0.451 values between -0.45 and -0.391 values between -0.39 and -0.341 values between -0.34 and -0.287 values between -0.28 and -0.2247 values between -0.22 and -0.17139 values between -0.17 and -0.11586 values between -0.11 and -0.051619 values between -0.05 and 0.011042 values between 0.01 and 0.07341 values between 0.07 and 0.1295 values between 0.12 and 0.1813 values between 0.18 and 0.248 values between 0.24 and 0.293 values between 0.29 and 0.351 values between 0.58 and 0.64offnegativepositiveoften

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. rient
  2. 吠
  3. nier
  4. erset
  5. 出汗
  6. .class
  7. ndef
  8. 成立以来
  9. кри
  10. ijd

Suppresses

  1. nhắc
  2. 桃
  3. thủ
  4. thẩm
  5. Step
  6. Pax
  7. :x
  8. +x
  9. atorial
  10. ally