word completing an institution name
A neuronOne of thousands of tiny dials inside each layer. It reads the text so far and produces a number, its activation, that nudges what the model writes next. in layerOne step in the stack the text passes through. Qwen3-0.6B has 28 layers, each with 3,072 neurons. 1 of Qwen3-0.6B. Its strongest snippets are fairly consistent: several of them peak on the same token. It is featuredA neuron picked for the full treatment: steering outputs and a written explanation. About 3,000 of the 86,000 neurons are 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 activationThe number a neuron produces for a token. Large positive means it fired hard; negative means it pushed the other way. was highest. Amber marks positive activation; the outlined tokenA piece of text the model reads at once: often a word, sometimes part of a word or a punctuation mark. is the peak. Hover a token for its strength.
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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
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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
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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.,
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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
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.” 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
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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
SteeringAdding a push along a neuron while the model writes, to see how its output changes. Turning it up or down.
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.
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.
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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
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. 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
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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
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.⏎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 mapWhich neuronsOne of thousands of tiny dials inside each layer. It reads the text so far and produces a number, its activation, that nudges what the model writes next. in earlier layersOne step in the stack the text passes through. Qwen3-0.6B has 28 layers, each with 3,072 neurons. feed this one, and which later ones it feeds. Amber links excite, blue links suppress; longer bars are stronger.
Fed by earlier layers
- L0:1224 suppresses
- L0:178 suppresses
- L0:1301 suppresses
- L0:893 weakly excites
- L0:34 weakly excites
- L0:1403 weakly suppresses
- L0:581 weakly excites
- L0:952 weakly suppresses
- L0:2517 weakly excites
- L0:1 weakly suppresses
- L0:1456 weakly excites
- L0:1144 weakly excites
- L0:968 weakly suppresses "and" joining two nouns
- L0:2474 weakly suppresses
- L0:737 weakly suppresses
- L0:182 weakly excites
- L0:1008 weakly suppresses
- L0:26 weakly suppresses
- L0:281 weakly excites
- L0:569 weakly excites
- L0:2589 weakly suppresses
- L0:1572 weakly excites
- L0:1407 weakly suppresses
- L0:2920 weakly suppresses
Feeds later layers
- L2:901 suppresses
- L3:334 suppresses
- L10:505 weakly excites
- L14:2217 weakly suppresses
- L11:455 weakly suppresses
- L13:2474 weakly suppresses
- L24:2988 weakly suppresses
- L17:2287 weakly suppresses
- L11:1365 weakly excites
- L7:1089 weakly suppresses
- L8:254 weakly suppresses
- L10:1762 weakly excites
- L5:1219 weakly suppresses
- L14:1104 weakly suppresses
- L7:399 weakly suppresses laboratory and research facility terms
- L17:975 weakly suppresses
- L24:1210 weakly suppresses
- L9:2291 weakly suppresses
- L8:2094 weakly excites
- L9:2486 weakly suppresses
- L3:427 weakly suppresses
- L9:1869 weakly suppresses
- L5:1350 weakly suppresses
- L9:951 weakly suppresses
Activation histogramA chart of how often a neuron takes each activation value.
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.
Logit lensReading which output tokens a neuron pushes toward or away from, straight off its output weights, before the later layers have their say.
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 layersOne step in the stack the text passes through. Qwen3-0.6B has 28 layers, each with 3,072 neurons. instead.
Promotes
- .NET
- 齿
- .ttf
- igner
- isors
- imate
- iator
- apper
- 指甲
- Entries
Suppresses
- eward
- ambi
- ��
- ongyang
- 院
- borrowed
- .Factory
- shaw
- 实验室
- /MIT