Neuron Explorer

Qwen3-0.6B

word completing an institution name

A neuron in layer 1 of Qwen3-0.6B. Its strongest snippets are fairly consistent: several of them peak on the same token. It is featured, so it has steering outputs.

What this neuron does

This neuron fires on the last word of an organisation's name, such as 'Oxford University Press', 'National Library' or 'international consortium'. It works in the opposite direction on phrases like 'funded by' and 'supported by', where it is strongly negative. Turning it up did not produce a clear visible theme.

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

    what surprised you most...<|endoftext|>Biggles Sees It Through⏎|Published||Aug-41 - Oxford University Press [H/B]|⏎Oxford University Press⏎[view publishing history]⏎|20 Images Online|⏎(48 votes

  2. #2 peak

    sessions at the January and July residencies. LibGuides: Commerce Research Guide: Where can find journal ...⏎Functioning as a research and publishing network, ScienceOpen offers open access to more than 28 million articles in all areas of science

  3. #3 peak

    arkers in tracking neuronal recovery, which may be associated with duration of [return to sport],” wrote Cassandra L. Pattinson, PhD, of the University of Queensland, Brisbane, Australia, and the National Institutes of Health, Bethesda, Md.,

  4. #4 peak

    to identify those who have the disease.⏎How can we contribute?⏎Oxford is leading CRyPTIC—Comprehensive Resistance Prediction in Tuberculosis: an International Consortium— as part of this effort. We hope to have a massive impact on improving

  5. #5 peak

    .” Where did this “charge” come from? The work was “led by the Council of Chief State School Officers (CCSSO) and the National Governors Association (NGA).” My question is this: When did Montana begin to be

  6. #6 peak

    related to a medical illness or a side effect from an herbal medicine. Those who take herbal products should also keep a reliable, unbiased reference on hand. The National Library of Medicine and National Institutes of Health offer a comprehensive, free Internet resource that can

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 need to be able to do this, I need to be able to do this. But I have been thinking about lately... (this is a bit of a problem to solve) I need to be able to do this, I need

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

    z, a former CU-Boulder postdoctoral researcher; and Peter Achermann, a sleep researcher at the University of Zurich in Switzerland.⏎The study was funded by the National Institute of Mental Health, Sepracor Inc. and the Swiss

  2. #2 peak

    . Even though the approach is computationally intensive and comparably expensive, it shows promise for the future of electric vehicles and the aerospace industry. This research is supported by the Grainger Center for Electric Machinery and Electromechanics.<|endoftext|>This

  3. #3 peak

    results reinforce the need for traditional preparation methods to take different toxicity levels into account when choosing the appropriate solvent for the preparation of a medicinal remedy. The study was funded by grants from the National Institutes of Health

  4. #4 peak

    .⏎Xuexin Duan, School of Precision Instrument and Opto-electronics Engineering, Tianjin University, China⏎Weihua Guan, School of<|endoftext|>The flu is everywhere, with influenza reported in all 50 states,

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. L0:1224 suppresses
  2. L0:178 suppresses
  3. L0:1301 suppresses
  4. L0:893 weakly excites
  5. L0:34 weakly excites
  6. L0:1403 weakly suppresses
  7. L0:581 weakly excites
  8. L0:952 weakly suppresses
  9. L0:2517 weakly excites
  10. L0:1 weakly suppresses
  11. L0:1456 weakly excites
  12. L0:1144 weakly excites
  13. L0:968 weakly suppresses "and" joining two nouns
  14. L0:2474 weakly suppresses
  15. L0:737 weakly suppresses
  16. L0:182 weakly excites
  17. L0:1008 weakly suppresses
  18. L0:26 weakly suppresses
  19. L0:281 weakly excites
  20. L0:569 weakly excites
  21. L0:2589 weakly suppresses
  22. L0:1572 weakly excites
  23. L0:1407 weakly suppresses
  24. L0:2920 weakly suppresses

Feeds later layers

  1. L2:901 suppresses
  2. L3:334 suppresses
  3. L10:505 weakly excites
  4. L14:2217 weakly suppresses
  5. L11:455 weakly suppresses
  6. L13:2474 weakly suppresses
  7. L24:2988 weakly suppresses
  8. L17:2287 weakly suppresses
  9. L11:1365 weakly excites
  10. L7:1089 weakly suppresses
  11. L8:254 weakly suppresses
  12. L10:1762 weakly excites
  13. L5:1219 weakly suppresses
  14. L14:1104 weakly suppresses
  15. L7:399 weakly suppresses laboratory and research facility terms
  16. L17:975 weakly suppresses
  17. L24:1210 weakly suppresses
  18. L9:2291 weakly suppresses
  19. L8:2094 weakly excites
  20. L9:2486 weakly suppresses
  21. L3:427 weakly suppresses
  22. L9:1869 weakly suppresses
  23. L5:1350 weakly suppresses
  24. L9:951 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 -2.07 and -2.001 values between -1.73 and -1.661 values between -1.39 and -1.321 values between -1.12 and -1.051 values between -0.85 and -0.781 values between -0.78 and -0.711 values between -0.71 and -0.642 values between -0.64 and -0.571 values between -0.57 and -0.502 values between -0.44 and -0.375 values between -0.37 and -0.3015 values between -0.30 and -0.2330 values between -0.23 and -0.16122 values between -0.16 and -0.10546 values between -0.10 and -0.031951 values between -0.03 and 0.04708 values between 0.04 and 0.11298 values between 0.11 and 0.18124 values between 0.18 and 0.2550 values between 0.25 and 0.3129 values between 0.31 and 0.3814 values between 0.38 and 0.452 values between 0.45 and 0.521 values between 0.52 and 0.591 values between 0.59 and 0.65offnegativepositiveoften

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. .NET
  2. 齿
  3. .ttf
  4. igner
  5. isors
  6. imate
  7. iator
  8. apper
  9. 指甲
  10. Entries

Suppresses

  1. eward
  2. ambi
  3. ��
  4. ongyang
  5. 院
  6. borrowed
  7. .Factory
  8. shaw
  9. 实验室
  10. /MIT