gap before a year in citations
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. 13 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 the blank spot just before the year in author-date citations such as "(Castaneda 1998)" or "(Courneya, Estabrooks & Nigg 1997)". Turning it up or down did not change the text in a way that relates to citations.
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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where_x, float where_y, float where_z);⏎void deallocate_model(model_3d_ref kill_this);⏎The compiler doesn't read your code like this
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eligible for the National Register of Historic Places.⏎The state of Wyoming did not concur and recommended further work before a⏎determination was made (Stephanson 1992).
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by the tour operator. It ensures safeguards and security of passengers and their luggages and provides remedies against damages to passengers (Van Hoof and Pennings, 2018).⏎Air Transport Law: Air transport law legislation aims safety of
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exercise program tend to be the individuals who fail to realize their exercise intentions…⏎(Marcus, Forsyth, Stone, Dubbert, McKenzie, Dunn & Blair 2000) This lack of physical activity among the elderly is of even
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⏎f :: Bool -> [Int]⏎f b = if b then xs else ⏎-- With library⏎g :: Bool -> [Int]⏎g = mwhen xs⏎See? It’s an amazing 14 characters shorter!⏎The current version
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intention has generally been insignificant among older and younger adults. (Courneya, Estabrooks & Nigg 1997) Unlike attitude, which tends to consistently account for approximately
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 have been thinking about the idea of a 2000 year ago a human being have 2000 years of freedom, a human being have 2000 years of freedom. a human being have 2
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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disappear when solutions are available for black holes embedded in arbitrary backgrounds.⏎|Original language||English (US)|⏎|Number of pages||12|⏎|Journal||Classical and Quantum Gravity|⏎|State||Published - Jul 7 2
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access all content.<|endoftext|>Great Slaty becomes World's Largest Woodpecker as Ivory Billed Goes Extinct⏎22 November 2021 | Vibhav peri | Crises⏎The Great Slaty Woodpecker
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of Text Reinterpretation Skill.⏎Bonitatibus, Gary; Beal, Carole R.⏎Four studies investigated when children became able to detect that the words
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active components of DST can be replicated in other school environments.⏎Source: Health Behavior and Policy Review, Volume 8, Number 4, July 2021, pp. 281
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
- L9:1159 suppresses
- L10:406 excites
- L10:2372 excites
- L3:436 excites
- L12:1535 excites
- L6:276 suppresses
- L12:2178 excites
- L7:244 excites
- L6:425 excites
- L2:1642 weakly excites
- L10:893 weakly suppresses
- L1:1878 weakly suppresses
- L10:1002 weakly excites
- L11:1479 weakly suppresses
- L11:1342 weakly excites
- L6:1775 weakly suppresses
- L3:488 weakly suppresses
- L1:919 weakly suppresses
- L6:514 weakly suppresses
- L10:487 weakly excites
- L11:2244 weakly excites
- L10:1275 weakly excites
- L12:1136 weakly suppresses
- L11:2780 weakly excites
Feeds later layers
- L15:2095 excites
- L16:2162 excites
- L16:1337 excites
- L18:2343 excites
- L17:2174 suppresses
- L14:1924 excites
- L18:1524 excites
- L26:236 excites
- L15:694 suppresses
- L16:1968 excites
- L16:650 suppresses
- L14:653 weakly suppresses
- L15:1893 weakly excites
- L18:862 weakly excites hedges like 'it turns out' and 'if any'
- L17:2586 weakly suppresses
- L20:844 weakly excites
- L14:726 weakly excites
- L18:1420 weakly excites
- L14:257 weakly excites
- L14:2363 weakly suppresses
- L19:1711 weakly excites
- L15:2284 weakly excites
- L16:949 weakly suppresses
- L21:1059 weakly excites
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
- ,json
- wert
- )⏎⏎⏎
- ียม
- يف
- ) ⏎ ⏎ ⏎
- 纶
- licher
- 这是一个
- oref
Suppresses
- %'⏎
- igsaw
- orphic
- соглас
- thử
- %";⏎
- éli
- ปรากฏ
- %'
- 自由