Neuron Explorer

Qwen3-0.6B

'of' after an abstract noun

A neuron in layer 12 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 'of' (or 'to') right after a noun like 'concept', 'idea' or 'knowledge', where the next words name the topic. It went quiet, and sometimes negative, on 'for' in phrases like 'a physical keyboard for transcription'. Turning it up or down gave unrelated 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

    or variables. The concept of correlation was employed to decide whether a significant relationship existed between the paired data. Furthermore

  2. #2 peak

    test hypotheses and make predictions. You'll use Excel's Analysis Toolpak to perform t-tests as well as simple linear and multiple regression analysis.⏎required: basic knowledge of Excel; see Excel Basics⏎Monday, Oct. 13, 6

  3. #3 peak

    of instruction where attention is given both to the language and the content” (Coyle et al 2010:3).⏎Historically, the idea of combining content and language learning (CLIL) comes from countries such as the USA

  4. #4 peak

    7 2003|⏎ASJC Scopus subject areas⏎- Physics and Astronomy (miscellaneous)<|endoftext|>Most computer users are familiar with the concept of spyware — at

  5. #5 peak

    free of processed and cooked food. Most raw food devotees also consume a mostly organic foods to avoid exposure to pesticides and other synthetic chemicals. The extent of adherence to these tenants is pending the level of commitment to adopting a “pure” version of

  6. #6 peak

    to the mischief-making followers of those gods.⏎Polytheistic or non-literate cultures very often contain a belief 1n winged minor gods but the concept of the intermediary, wholly good angel was most fully developed in the West. Where there

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 20th of the 10th, the 10th of the 10th of the the 1 100th, the the 10th of the the 100

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

    that fail to enter the system for annualized screening is closer to 70%, a leading contributor for breast cancer being the number #1 cause of cancer mortality for Asian women.⏎On all tissue types, of those patients who are diagnosed by mamm

  2. #2 peak

    with a Veritas Prep instructor for a time, it’s a good idea for students to take another practice test.

  3. #3 peak

    the conditions.<|endoftext|>Viewing page 28 of 101⏎It looks like you're using a mobile device. We recommend using a physical keyboard for transcription entry.⏎28 REPORT NATIONAL ADVISORY COMMITTEE FOR AERON

  4. #4 peak

    Exercise 6.5⏎In NCERT Solutions for Class 10 Maths Chapter 6 Exercise 6.5, we have

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. L4:4 suppresses
  2. L10:132 excites
  3. L11:31 suppresses
  4. L3:278 excites
  5. L5:5 weakly suppresses digit after a label like paper or type
  6. L7:8 weakly excites
  7. L6:345 weakly excites
  8. L0:1082 weakly suppresses
  9. L7:6 weakly suppresses
  10. L1:1300 weakly excites
  11. L9:29 weakly excites opening parenthesis before an acronym
  12. L9:1358 weakly excites
  13. L0:2832 weakly excites
  14. L10:189 weakly excites
  15. L6:1342 weakly excites
  16. L10:105 weakly suppresses
  17. L10:272 weakly suppresses
  18. L3:232 weakly excites 'on' after a noun like 'impact on'
  19. L4:16 weakly excites
  20. L4:1686 weakly excites
  21. L9:11 weakly excites
  22. L0:700 weakly suppresses
  23. L4:2923 weakly excites
  24. L5:871 weakly excites

Feeds later layers

  1. L22:489 suppresses
  2. L16:567 excites
  3. L16:109 excites
  4. L19:1464 suppresses
  5. L16:162 excites
  6. L17:1122 suppresses
  7. L16:507 excites
  8. L16:153 weakly excites
  9. L16:194 weakly excites
  10. L16:25 weakly excites
  11. L16:73 weakly excites
  12. L17:2196 weakly suppresses
  13. L13:132 weakly suppresses "of" after a noun
  14. L22:171 weakly suppresses
  15. L16:107 weakly excites
  16. L17:1223 weakly suppresses
  17. L16:127 weakly excites
  18. L16:105 weakly excites
  19. L16:110 weakly excites
  20. L16:53 weakly excites
  21. L16:549 weakly excites
  22. L16:26 weakly excites
  23. L15:2573 weakly suppresses
  24. L16:1040 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 -5.65 and -5.461 values between -5.46 and -5.282 values between -4.90 and -4.712 values between -4.71 and -4.521 values between -4.52 and -4.333 values between -4.33 and -4.142 values between -4.14 and -3.955 values between -3.95 and -3.773 values between -3.77 and -3.586 values between -3.58 and -3.393 values between -3.39 and -3.204 values between -3.20 and -3.017 values between -3.01 and -2.827 values between -2.82 and -2.638 values between -2.63 and -2.448 values between -2.44 and -2.269 values between -2.26 and -2.0711 values between -2.07 and -1.889 values between -1.88 and -1.6923 values between -1.69 and -1.5020 values between -1.50 and -1.3129 values between -1.31 and -1.1233 values between -1.12 and -0.9330 values between -0.93 and -0.7553 values between -0.75 and -0.5655 values between -0.56 and -0.37156 values between -0.37 and -0.181144 values between -0.18 and 0.011434 values between 0.01 and 0.20680 values between 0.20 and 0.39141 values between 0.39 and 0.5811 values between 0.58 and 0.762 values between 0.76 and 0.951 values between 0.95 and 1.141 values between 1.14 and 1.332 values between 1.52 and 1.711 values between 1.71 and 1.90offnegativepositiveoften

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. 诱人
  2. 子里
  3. etable
  4. 是韩国
  5. isable
  6. ining
  7. oystick
  8. ensen
  9. -double
  10. obby

Suppresses

  1. depth
  2. depth
  3. begin
  4. shore
  5. prime
  6. shi
  7. maturity
  8. conscious
  9. suspense
  10. اب