Neuron Explorer

Qwen3-0.6B

'result' and 'results from' in science prose

A neuron in layer 2 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 fires weakly on phrases like 'a famous result of Gauss' and 'the results from'. It also dips on the endings of some Russian surnames. Turning it up or down did not give a clear change.

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

    0, 1, depending on the quadratic residue properties of modulo .⏎A famous result of Gauss states that when the modulus is a prime , the two sums and have

  2. #2 peak

    erosion intensities. A practical application of this measurement technique was demonstrated in testing the viability of air injection as a means of mitigating cavitation erosion. The results from the impulse pressure measurements were compared with those obtained from hydrophone and accelerometer measurements.

  3. #3 peak

    the origin, takes steps given by the terms of the exponential or quadratic residue Gauss sum modulo , and ends at the value of the Gauss sum. By a famous result of Gauss, if the modulus is a prime number, the two walks always end

  4. #4 peak

    active. In principle, a passive tracer blindly follows the fluid phase in which it is injected. Interpretation of tracer-production curves must account for this. The results from the application of active tracers may give information about fluid saturation and rock surface

  5. #5 peak

    : conductive electrodes coated with a compound called polyanthraquinone, which has a natural chemical attraction<|endoftext|>From: Michael Barrie <mibarrieinterchange.ubc.ca>⏎Subject: Overt Markers on Mass N

  6. #6 peak

    90 days following lively shooter drills, in contrast with the 90 days earlier than the drills.⏎The authors of this research, together with Mai ElSherief, PhD, drew these conclusions after analyzing 54 million social media posts earlier

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: In the, you are, the first, you are: The world is full of the, you have is: A long. The. This. In mathematics, You is Contemporary and 10000.

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

    , Salyut 6 EO-1, Salyut 7 EP-5. More...⏎Makarov Makarov, Oleg Grigoryevich (1933-20

  2. #2 peak

    eneration of multi-excitons via virtual single-exciton states; Richard D. Schaller, Vladimir M. Agranovich and Victor I. Klimov; Nature Physics 1, 189<|endoftext|>d.175

  3. #3 peak

    It would have taken the pen of a Kafka . . . to depict the world of visas in all its surrealistic absurdity; that of a Dostoyevsky to render the nightmare of the petitioners’ struggle for survival.” Kaplan is

  4. #4 peak

    18.⏎More... - Chronology...⏎First Launch: 1972 Early.⏎Lazarev Lazarev, Vasili Grigoryevich (1928-1990) Russian physician cosmon

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. L1:1779 weakly suppresses
  2. L1:3038 weakly excites
  3. L0:292 weakly suppresses
  4. L1:2683 weakly excites
  5. L1:865 weakly suppresses
  6. L1:455 weakly excites start-of-document end token
  7. L1:491 weakly excites
  8. L1:171 weakly excites "but" after a negated clause
  9. L1:1099 weakly excites
  10. L1:348 weakly excites
  11. L0:1655 weakly suppresses
  12. L0:1224 weakly suppresses
  13. L1:934 weakly suppresses
  14. L0:1513 weakly excites
  15. L0:823 weakly suppresses
  16. L0:1984 weakly excites
  17. L1:2608 weakly suppresses
  18. L0:1317 weakly excites
  19. L1:1464 weakly excites
  20. L0:2755 weakly suppresses
  21. L0:178 weakly suppresses
  22. L0:453 weakly suppresses
  23. L0:1876 weakly excites
  24. L0:2947 weakly excites

Feeds later layers

  1. L17:947 suppresses
  2. L6:2649 suppresses
  3. L7:1290 suppresses
  4. L9:436 suppresses
  5. L10:112 suppresses
  6. L23:2890 suppresses
  7. L9:453 excites
  8. L22:2550 weakly suppresses
  9. L7:295 weakly suppresses
  10. L16:2420 weakly suppresses
  11. L16:2354 weakly suppresses
  12. L17:2381 weakly excites
  13. L23:276 weakly suppresses
  14. L17:714 weakly suppresses
  15. L15:2050 weakly excites
  16. L14:2955 weakly excites
  17. L19:891 weakly suppresses
  18. L14:1199 weakly suppresses
  19. L22:2247 weakly excites
  20. L14:2324 weakly suppresses
  21. L20:2663 weakly excites
  22. L5:2841 weakly suppresses
  23. L19:2956 weakly excites
  24. L14:2851 weakly suppresses

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 -1.30 and -1.242 values between -0.87 and -0.801 values between -0.80 and -0.742 values between -0.74 and -0.683 values between -0.62 and -0.555 values between -0.55 and -0.496 values between -0.49 and -0.437 values between -0.43 and -0.3717 values between -0.37 and -0.3050 values between -0.30 and -0.2497 values between -0.24 and -0.18260 values between -0.18 and -0.12565 values between -0.12 and -0.061264 values between -0.06 and 0.01971 values between 0.01 and 0.07374 values between 0.07 and 0.13177 values between 0.13 and 0.1953 values between 0.19 and 0.2625 values between 0.26 and 0.3210 values between 0.32 and 0.382 values between 0.38 and 0.446 values between 0.44 and 0.514 values between 0.51 and 0.573 values between 0.57 and 0.631 values between 0.63 and 0.691 values between 0.76 and 0.821 values between 1.13 and 1.19offnegativepositiveoften

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. ece
  2. è
  3. �
  4. emp
  5. awei
  6. horse
  7. riage
  8. owered
  9. horse
  10. ò

Suppresses

  1. 镒
  2. onas
  3. hausen
  4. 社会资本
  5. 莫斯科
  6. loh
  7. RYPT
  8. Siber
  9. ROM
  10. pered