Neuron Explorer

Qwen3-0.6B

row and column words in grids and tables

A neuron in layer 6 of Qwen3-0.6B. Its strongest snippets are mixed: they peak on different tokens. It is featured, so it has steering outputs.

What this neuron does

This neuron lights up on words that describe the layout of a table or grid, such as row, column, across, and vertical, especially in spreadsheet lookups and number puzzles. When it was turned up, the model kept drifting into talk about rows, columns and matrices.

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

    puzzle challenges students to use the numbers provided to help them fill in the blank squares so that each number, 1 to 9, appears in every Column, Row, and Block of the completed puzzle.⏎Click for a

  2. #2 peak

    UP (click here for more information).⏎What is a 2D lookup?⏎In many cases, you only look for a value in – let’s say – column A and return the

  3. #3 peak

    general amount, divided by the letter and the number of the cell with the percentage.⏎But for Excel to perform the calculation, this must be placed in the cell where we want the result.<|endoftext|>Designing home landscapes to be: Ecologically rich

  4. #4 peak

    3rd rows show cells that have been treated with ASOs. The red dye is nearly all

  5. #5 peak

    and development; women<|endoftext|>There are many cases in which you need a 2 dimensional lookup. That means, if you want to get a value from a specific row-column combination with neither rows or

  6. #6 peak

    UN committee asked the Australian Government to report back to it in detail in the<|endoftext|>Discover the words hidden in the grid, written through one another in eight horizontal, vertical and diagonal directions. Select words by clicking on the first and last letters, in

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: when are you, kid? The question is, are you in the mood to come? Okay, the answer is... well, the answer is... wait, the answer is... the answer is... the answer is... the answer is...

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

    major work that tried to put the Revolution into a broader political and social framework.⏎See E. Chill, Power, Property, and History: Barnave's Introduction to the French Revolution and Other Writings (1971).⏎The Columbia

  2. #2 peak

    example:⏎s1 = 'Hello, this is Tom's laptop' >>> Output: >>> s1 = 'Hello, this is Tom's laptop' File "", line 1 s1 = 'Hello, this is Tom's laptop'⏎```The

  3. #3 peak

    19barn). It is estimated neutrino cross-section for interaction increases linearly with energy of incident neutrino.⏎Reference: Griffiths, David, Introduction to Elementary Particles, Wiley, 1987.⏎See also: Ant

  4. #4 peak

    0, $20, $50, and $100 denominations.⏎Adding money is easy as long as it is remembered that money is added in the same way that decimals are added. Money is represented as a decimal, with

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. L3:2336 excites
  2. L5:102 excites
  3. L5:94 weakly suppresses
  4. L5:28 weakly excites
  5. L3:2044 weakly excites
  6. L5:158 weakly suppresses
  7. L5:110 weakly suppresses
  8. L5:133 weakly excites
  9. L2:126 weakly excites
  10. L3:1924 weakly suppresses
  11. L5:141 weakly excites
  12. L5:2036 weakly suppresses
  13. L0:1607 weakly suppresses
  14. L5:169 weakly excites
  15. L5:117 weakly excites
  16. L0:3010 weakly excites
  17. L5:86 weakly suppresses
  18. L3:2310 weakly excites
  19. L4:783 weakly suppresses
  20. L2:45 weakly excites
  21. L4:540 weakly excites
  22. L5:60 weakly excites
  23. L5:2938 weakly suppresses
  24. L4:1767 weakly suppresses

Feeds later layers

  1. L19:1324 excites
  2. L10:1200 excites
  3. L7:2701 excites
  4. L7:1606 excites
  5. L7:2918 excites
  6. L11:2966 excites
  7. L7:2118 suppresses
  8. L12:2937 excites
  9. L9:3012 excites
  10. L22:1053 weakly excites
  11. L9:2527 weakly excites
  12. L9:1729 weakly excites
  13. L11:1270 weakly excites
  14. L9:1095 weakly excites
  15. L9:812 weakly excites
  16. L10:1709 weakly suppresses
  17. L8:1631 weakly excites
  18. L8:2167 weakly suppresses
  19. L8:1593 weakly excites
  20. L23:1781 weakly excites
  21. L15:2545 weakly suppresses
  22. L7:2997 weakly excites
  23. L17:2351 weakly suppresses
  24. L9:882 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 -0.58 and -0.552 values between -0.47 and -0.452 values between -0.45 and -0.426 values between -0.42 and -0.392 values between -0.39 and -0.376 values between -0.37 and -0.349 values between -0.34 and -0.3210 values between -0.32 and -0.2922 values between -0.29 and -0.2617 values between -0.26 and -0.2433 values between -0.24 and -0.2161 values between -0.21 and -0.1978 values between -0.19 and -0.16102 values between -0.16 and -0.13162 values between -0.13 and -0.11172 values between -0.11 and -0.08264 values between -0.08 and -0.06335 values between -0.06 and -0.03499 values between -0.03 and -0.00544 values between -0.00 and 0.02423 values between 0.02 and 0.05358 values between 0.05 and 0.07212 values between 0.07 and 0.10184 values between 0.10 and 0.13138 values between 0.13 and 0.1584 values between 0.15 and 0.1859 values between 0.18 and 0.2039 values between 0.20 and 0.2330 values between 0.23 and 0.2628 values between 0.26 and 0.287 values between 0.28 and 0.315 values between 0.31 and 0.332 values between 0.33 and 0.365 values between 0.36 and 0.392 values between 0.39 and 0.414 values between 0.41 and 0.441 values between 0.44 and 0.46offnegativepositiveoften

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. newRow
  2. COLUMN
  3. (column
  4. (rank
  5. оф
  6. ROW
  7. rif
  8. COLUMN
  9. rowIndex
  10. nrows

Suppresses

  1. gether
  2. ้าง
  3. pliant
  4. 概念
  5. itational
  6. Concepts
  7. ubectl
  8. ragments
  9. plier
  10. 保留