Neuron Explorer

Qwen3-0.6B

'that' after a finding or surprise verb

A neuron in layer 6 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 word 'that' when it introduces a clause after a verb of finding, learning or evidence, as in 'you may be shocked to learn that' or 'it's not surprising that'. Its opposite side is on words of belief, such as 'believed', 'believe' and 'sure of'. Turning it up did not give a clear theme in the sample 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

    ZZs like Aspilche. We asked her about how she’s managing after the first year of knowing she has Alpha 1.⏎How did you discover that you had it?⏎For about two years prior to this confirmation, I was diagnosed

  2. #2 peak

    build-up. The third and most important strategy is HEPA air filtration.⏎HEPA Air Purification⏎A HEPA air<|endoftext|>You may be shocked to learn that in England alone, people take 3 billion car trips for less

  3. #3 peak

    Ste. Genevieve Plant has joined it. It’s not surprising that the list hasn’t changed much – major industrial plants like these aren’t built every

  4. #4 peak

    with a broader body of work indicating a profound impact of climate change on precisely these sorts of events.”⏎The new normal⏎“This analysis confirms what we already know – that we are suffering an extreme weather event caused by climate change,” says Gareth Redmond

  5. #5 peak

    much and in what ways we trust AI in the workplace, how we view the risks and benefits, and what is expected for AI to be trusted. We find that only one in two employees are willing to trust AI at work. Their attitude depends

  6. #6 peak

    their fat cells detected more insulin resistance in the women who ate the high-GI diet. It’s hardly surprising, then, that several large population studies have shown that people who eat diets filled with low-fibre

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 new problem, the same level of difficulty, the same level of difficulty, and so on, if there is an extra problem, the same level of difficulty, so, the same level of difficulty, so, the same level

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

    It is generally believed that profit earning is the primary objective of business. However, as per modern thinking

  2. #2 peak

    anyone how long the interruption would last. But with her intimate knowledge of volcanic ash, and a good idea of what it does to jet engines, she was sure of one thing: “I wouldn’t want to get on a plane right now.”⏎

  3. #3 peak

    indicating that the head bearing Pharaoh Khafre's likeness could have been carved out of a larger lion's head. These points led some researchers to believe that the Sphinx could have been built much earlier by a more ancient civilization, thus

  4. #4 peak

    intuitive. I certainly can’t claim to be a perfect listener. All I can say is that I’m learning and getting better.⏎We all know, of course, that listening and hearing are required in order to understand the heart of what the “

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. L5:1807 suppresses
  2. L4:2495 suppresses
  3. L5:2364 suppresses
  4. L4:1382 excites
  5. L4:3054 excites
  6. L4:730 weakly excites
  7. L4:2893 weakly excites the word 'means' after a subject
  8. L4:2451 weakly excites
  9. L2:775 weakly suppresses
  10. L0:101 weakly suppresses
  11. L1:420 weakly excites
  12. L4:793 weakly suppresses
  13. L2:2648 weakly suppresses
  14. L5:3034 weakly suppresses
  15. L4:2692 weakly excites
  16. L5:740 weakly excites
  17. L3:1356 weakly excites
  18. L2:1293 weakly excites
  19. L0:623 weakly suppresses
  20. L4:2135 weakly suppresses
  21. L0:2607 weakly suppresses
  22. L5:2134 weakly suppresses
  23. L5:1979 weakly excites
  24. L3:2061 weakly excites

Feeds later layers

  1. L7:751 strongly suppresses
  2. L8:132 excites
  3. L14:655 excites
  4. L8:615 excites
  5. L13:3 suppresses
  6. L15:1702 excites
  7. L7:7 suppresses
  8. L7:135 excites 'of' after 'issue' in citations
  9. L12:896 excites
  10. L9:330 excites gap where a number was removed
  11. L14:830 excites
  12. L15:27 excites
  13. L18:867 excites
  14. L15:1028 excites
  15. L17:1282 excites
  16. L17:2213 excites
  17. L8:361 excites
  18. L16:1303 weakly excites 'that' starting a clause after a noun
  19. L16:1219 weakly excites
  20. L16:797 weakly suppresses
  21. L14:531 weakly suppresses
  22. L17:2426 weakly suppresses 'that' after nouns of belief or fact
  23. L21:2876 weakly suppresses
  24. L18:509 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.

1 values between -4.11 and -3.941 values between -2.62 and -2.451 values between -1.95 and -1.791 values between -1.79 and -1.621 values between -1.62 and -1.464 values between -1.46 and -1.293 values between -1.29 and -1.135 values between -1.13 and -0.962 values between -0.96 and -0.796 values between -0.79 and -0.6313 values between -0.63 and -0.4634 values between -0.46 and -0.30262 values between -0.30 and -0.131846 values between -0.13 and 0.031404 values between 0.03 and 0.20281 values between 0.20 and 0.3721 values between 0.37 and 0.535 values between 0.53 and 0.707 values between 0.70 and 0.864 values between 0.86 and 1.032 values between 1.19 and 1.362 values between 1.36 and 1.521 values between 1.52 and 1.691 values between 2.35 and 2.52offnegativepositiveoften

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. ński
  2. 过去的
  3. يح
  4. .handlers
  5. _LANG
  6. listened
  7. anie
  8. 师事务所
  9. anje
  10. Actual

Suppresses

  1. cline
  2. fr
  3. CC
  4. ib
  5. なく
  6. sworth
  7. im
  8. lining
  9. /se
  10. 使我