Neuron Explorer

Qwen3-0.6B

comma ending an 'if' clause

A neuron in layer 20 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 comma at the end of a sentence's opening 'If' clause, such as 'If the borrower already holds property,'. Its negative side reacts to question words that start a question, like 'What' and 'Where'. Turning it up made the model repeat question words like 'why' and 'should'.

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

    stress test, the borrower can make efforts to pay off their existing loans or reduce their outstanding debt before applying for a mortgage loan.⏎If the borrower already holds property, the lender will take into account their existing property and mortgage when conducting the stress test

  2. #2 peak

    the lack of specific information in the standards. If we are revising a draft of social studies standards, we should not be focusing on the cultural self-awareness of a student. I

  3. #3 peak

    draw any prehistoric scene you’d like. But the trick is that you have use the entire sheet of paper and not leave any spots blank. It sounds simple, but it can get tricky depending on what you choose to draw.⏎Here are some

  4. #4 peak

    both upper and lower case letters⏎- Use more special characters⏎- Make the way you combine them more complicated<|endoftext|>If unwed parents are going to get married, the best window of opportunity for that union seems to be before their child turns

  5. #5 peak

    caregivers provide important opportunities to observe, learn, and practice healthy, adaptive responses to adverse experiences (<|endoftext|>If you've encountered anchovies on your Caesar salad or pizza, you might wonder what kind of fish it is. Anchovies are small, shiny

  6. #6 peak

    This weakens the cell wall and it ruptures resulting in the death of the bacteria.⏎If you miss a dose of Ampicillin and are taking it regularly, take it as soon as possible. If it is almost time for your next dose

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 idea of a single system of law, to be the very foundation of the entire economy and the public order in the entire society, and to be the only law in the entire system. The idea of a single law to be the only

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

    I might have what?”⏎She said: “A rare disease that is called Alpha 1 Antitrypsin Deficiency.”⏎I was confused. “What? What is this? How can I cure it? What do I do?”

  2. #2 peak

    infection spread from the coffin joint, and what does it cause?⏎- axially: footrot⏎- abaxially: vertical fissure aka sand crack⏎Where are septic

  3. #3 peak

    The term butterfly effect first appeared in his 1972 paper Predictability: Does the flap of a butterfly's wings in Brazil set off a tornado in Texas?.⏎Lorenz started to develop his theories of chaos as a meteorologist

  4. #4 peak

    2016? Are they trying to avoid having to answer questions about why their flawed analysis claims the HCP is somehow better for the environment? Or why they decided not to consider a science-based alternative by the Panther Review Team? Is

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. L18:2812 strongly excites
  2. L18:1586 strongly suppresses
  3. L17:3046 strongly suppresses answer labels and tag questions
  4. L15:2412 suppresses
  5. L13:2080 suppresses
  6. L19:2814 excites
  7. L12:1069 excites
  8. L17:1480 excites
  9. L16:2817 suppresses
  10. L14:1800 suppresses
  11. L16:1078 excites
  12. L11:296 suppresses
  13. L8:145 suppresses
  14. L14:441 excites
  15. L17:2579 suppresses
  16. L17:3071 excites
  17. L13:2701 excites
  18. L14:385 suppresses
  19. L6:1572 suppresses
  20. L5:1800 suppresses
  21. L17:2638 suppresses
  22. L13:2939 excites
  23. L15:1655 excites
  24. L15:2327 suppresses

Feeds later layers

  1. L21:728 strongly excites
  2. L27:656 strongly excites
  3. L21:1362 strongly excites
  4. L25:576 strongly excites
  5. L24:1439 strongly excites
  6. L21:1538 excites
  7. L22:2765 excites
  8. L23:594 excites
  9. L22:1414 excites
  10. L24:2138 excites comma before 'right?' tag
  11. L24:402 excites
  12. L23:320 excites
  13. L26:1046 excites
  14. L26:1836 excites
  15. L22:1933 excites
  16. L26:613 excites
  17. L21:262 suppresses
  18. L27:960 excites
  19. L26:1185 excites
  20. L25:962 excites
  21. L26:1097 excites
  22. L23:873 excites unclear: document ends and math commas
  23. L22:543 excites
  24. L21:2363 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 -14.04 and -13.291 values between -13.29 and -12.542 values between -11.04 and -10.291 values between -9.54 and -8.801 values between -8.80 and -8.051 values between -8.05 and -7.301 values between -7.30 and -6.551 values between -5.80 and -5.052 values between -5.05 and -4.301 values between -3.55 and -2.805 values between -2.80 and -2.0510 values between -2.05 and -1.30285 values between -1.30 and -0.553027 values between -0.55 and 0.20263 values between 0.20 and 0.9587 values between 0.95 and 1.7053 values between 1.70 and 2.4431 values between 2.44 and 3.1927 values between 3.19 and 3.9413 values between 3.94 and 4.6926 values between 4.69 and 5.4418 values between 5.44 and 6.1917 values between 6.19 and 6.949 values between 6.94 and 7.697 values between 7.69 and 8.447 values between 8.44 and 9.191 values between 9.19 and 9.944 values between 9.94 and 10.692 values between 10.69 and 11.432 values between 12.18 and 12.931 values between 15.18 and 15.93offnegativepositiveoften

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. 是否会
  2. how
  3. 会不会
  4. 是否
  5. why
  6. 有没有
  7. 是不是
  8. 是怎么
  9. 是否
  10. 是什么

Suppresses

  1. lessly
  2. ollower
  3. lastic
  4. ifiers
  5. eland
  6. ankan
  7. 绎
  8. conomy
  9. 鞭
  10. prung