Neuron Explorer

Qwen3-0.6B

"own" in reflexive phrases

A neuron in layer 15 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 is clearly about the word "own" in phrases like "their own", "its own" or "one's own". Turned up, the model kept writing "own" and "herself" and "itself" over and over, which matches what it reacts to.

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

    nature, since a thing cannot be its own cause. In other words, an object being the subject of its own self.⏎

  2. #2 peak

    in the world despite the most diligent and prolonged search in the fossil record.⏎In their attempts to gather evidence for evolution, evolutionists have unwittingly proven by their own efforts that evolution cannot have happened at all!⏎The person who originally put forward the

  3. #3 peak

    term human-computer interaction (HCI) implies. Computers today are no longer just tools that respond passively to directions but social agents that are online participants in their own right. Miller notes that if I hit my thumb with a hammer I blame myself

  4. #4 peak

    ule or what the circumstances, will be punished severely.⏎Zero tolerance didn't work for the drug war; the Customs program championed by Meese choked on its own absurdities, finally dying a quiet death after Customs agents attempted to seize a scientific

  5. #5 peak

    can be seen as being exploited⏎What is a narrative therapy?⏎Narrative therapy is a style of therapy that helps people become—and embrace being—an expert in their own lives In narrative therapy, there is an emphasis on the stories we develop and carry

  6. #6 peak

    models -- my father grew up as an out-of-wedlock only child -- does not necessarily determine one's fate or destiny. Sometimes one must become one's own role model, a responsibility made easier by following this prescription, originally printed in my

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: you can find, for example, the number of ways to add two integers, which is a multiple, and it is possible to be in the range of the number, and there, the number is a multiple, and in the case,

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

    electrical activity within glia to send messages and information. It was therefore assumed that glia were deaf and dumb, incapable of communicating with either neurons or other glia, and therefore not particularly compelling as a focus of research. A good analogue would

  2. #2 peak

    In fact, some historians have argued the exact opposite: the Soviet Union only lasted as long as it did because the Kremlin held up a foreign enemy to distract from internal pressures. Without a boogeyman to act as a unifying force paper

  3. #3 peak

    + 1 = 2. We then get the answer 524 Can we simplify? Yes, that's possible. 524 = 512.⏎The answer is 214 + 314 =

  4. #4 peak

    other examples of patterns you could use:⏎- Three letters, special character, three numbers⏎- Three numbers, special character, three letters⏎- Take a word

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. L7:1721 excites
  2. L14:1952 excites
  3. L10:2979 suppresses
  4. L12:2564 suppresses
  5. L13:2338 suppresses 'not' in 'if not' hedges
  6. L9:844 suppresses
  7. L14:2295 excites
  8. L9:3068 suppresses
  9. L12:2662 excites
  10. L12:2806 weakly suppresses
  11. L12:2230 weakly suppresses
  12. L14:2399 weakly excites
  13. L0:1565 weakly suppresses
  14. L9:1478 weakly suppresses
  15. L12:154 weakly suppresses
  16. L12:2739 weakly excites
  17. L12:671 weakly suppresses
  18. L11:585 weakly excites
  19. L10:2431 weakly excites
  20. L9:2320 weakly suppresses
  21. L0:2895 weakly excites
  22. L8:1451 weakly excites
  23. L11:1548 weakly excites
  24. L0:2672 weakly excites

Feeds later layers

  1. L17:1485 strongly excites
  2. L17:2572 excites
  3. L19:3014 excites
  4. L25:849 excites
  5. L22:643 excites
  6. L27:1381 excites
  7. L16:1921 excites
  8. L18:2772 excites
  9. L27:983 excites
  10. L18:2632 excites
  11. L17:1359 excites
  12. L25:2669 excites
  13. L18:1882 excites
  14. L18:1026 excites
  15. L19:1630 excites
  16. L18:2471 weakly excites
  17. L17:2975 weakly excites
  18. L20:2483 weakly suppresses
  19. L20:1833 weakly excites
  20. L22:2796 weakly excites
  21. L21:1316 weakly suppresses
  22. L16:1833 weakly excites 'who' after a name and title
  23. L20:2976 weakly suppresses
  24. L17:2240 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.

12 values between -1.26 and -0.91258 values between -0.91 and -0.561482 values between -0.56 and -0.211941 values between -0.21 and 0.14176 values between 0.14 and 0.4917 values between 0.49 and 0.848 values between 0.84 and 1.193 values between 1.19 and 1.544 values between 1.54 and 1.892 values between 1.89 and 2.242 values between 2.24 and 2.591 values between 2.94 and 3.301 values between 3.30 and 3.651 values between 12.41 and 12.76offnegativepositiveoften

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. itself
  2. themselves
  3. herself
  4. oneself
  5. 自己
  6. 自身
  7. himself
  8. 自己的
  9. ourselves
  10. 了自己的

Suppresses

  1. ales
  2. ICIENT
  3. ��
  4. panse
  5. Priority
  6. opolitan
  7. ensen
  8. owitz
  9. continuous
  10. liberal