opening parenthesis after a word
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. 18 of Qwen3-0.6B. Its strongest snippets are very consistent: they mostly 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 an opening bracket that follows a word and introduces a side note, a citation or a definition, such as 'ionization' in brackets. Its negative side is brackets inside author names and math. Turning it up did not produce a clear change in the 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 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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D) space is a complicated task, a challenge to both biological and artificial systems. Increasing the number of degrees of freedom of the arm makes this task more complicated (Hollerbach, 1990a), and yet most biological movements
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if maximum LST was higher in primary or in any of the additional time periods. For every time period, an individual data source should be selected (primary or additional).⏎Climate change has an impact on extreme heat waves and record high
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in files and, until recently, each new search request did a “full scan” on the content (slow and resource intensive – some notes here). The new indexer solves this problem and
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Kayak is spelled the same forward and backward.⏎Seen and Heard⏎What made you want to look up kayak? Please tell us where you read or heard it (including the quote, if possible).<|endoftext|>Healthy Food Water Color Art⏎Supplies
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. When heated, the atoms in the gas either gain or lose electrons (ionization) and the end result is a charged particle plasma. Packed full
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can no longer be accessed are eventually removed (see Garbage Collection).⏎Because it is common to perform arithmetic operations on a marker
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: ................................................................................................................................................
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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pixels of the two images.⏎Express MSE mathematically from the description in Step 1. We therefore have MSE = 1/mn [?? (I(i,j) - K(i,j))^2] where I and K are matrices that
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nine were found to be “obstructive.”<|endoftext|>Rural earthen roads impact assessment in Phewa watershed, Western region, Nepal⏎© The Author(s). 2016⏎Received: 23 November 20
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, II (MH)A, and IIIA) are given in ASTM C150. They correspond in composition to ASTM Types I, II, II(MH), and III, respectively, except that small quantities of air- entraining
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in a circle⏎(C) 2009 Copyright Math Open Reference. All rights reserved<|endoftext|>Use chain rule⏎F'(x) = dF(x)/dx = (dF(x)/dx2)(dx2/dx)
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
- L4:64 excites
- L17:304 excites opening parenthesis after a claim
- L1:102 excites
- L10:142 suppresses opening parenthesis mid-sentence
- L16:1143 suppresses
- L14:90 suppresses
- L3:10 excites
- L5:275 excites
- L12:5 excites
- L0:11 excites
- L6:468 excites
- L4:2309 excites
- L9:2249 suppresses
- L0:86 excites
- L3:57 excites
- L0:1252 weakly suppresses
- L10:33 weakly suppresses
- L16:455 weakly excites
- L4:2958 weakly excites
- L7:432 weakly excites
- L14:415 weakly suppresses
- L16:439 weakly suppresses
- L9:339 weakly excites
- L16:844 weakly suppresses
Feeds later layers
- L20:306 suppresses
- L19:471 suppresses
- L19:1099 excites
- L22:765 suppresses
- L19:353 suppresses
- L23:191 suppresses
- L24:1486 suppresses
- L19:938 weakly excites
- L20:131 weakly suppresses
- L22:286 weakly suppresses
- L22:209 weakly suppresses
- L21:2808 weakly excites
- L20:597 weakly suppresses
- L21:3054 weakly excites
- L22:2639 weakly suppresses
- L27:990 weakly suppresses
- L20:1134 weakly suppresses
- L23:517 weakly suppresses
- L23:290 weakly suppresses
- L24:508 weakly suppresses
- L19:1133 weakly excites last word before end of document
- L19:2576 weakly excites
- L19:537 weakly suppresses
- L19:1037 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
- note
- )⏎⏎
- ogn
- nes
- )⏎
- aurus
- Note
- nas
- 记住
- Cs
Suppresses
- を開
- 所所
- ใจ
- ']]['
- ący
- iox
- 솥
- ügen
- ))-
- ��