'mean' after 'doesn't' in 'just because' sentences
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. 6 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 lights up on the word 'mean' in sentences like 'just because X doesn't mean Y', where a point is being qualified or pushed back on. Turning it up made the model drift into rambling text, with no clear 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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connected to the National Institute of Health, has some pretty amazing fact sheets that lay everything out in great detail. But just because supplements are safe in moderation doesn't mean that more is better. Combining
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of health benefits, including weight loss, improved lung function, lower risk of stroke, cancer and heart disease.⏎But just because the humble apple is ubiquitous doesn't mean it's without some mystery as well. Read on to learn more about the fruit
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consonant sounds work better throughout the melodic phrase. Just because a word or two fits the number of syllables you need to fill in your melody doesn't mean it will necessarily flow out nicely when sung
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to consider, such as job market demand, salary ranges, long-range opportunities, skills required, etc. Just because an occupation is "hot" now does not mean it will be equally in demand in 10 years or that your child has
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Also just because milk is rich in calcium doesn’t mean much if you don’t have vitamin D to accompany it, otherwise the calcium can
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try with your children.⏎1. Brainstorm ways to save and collect money.⏎Your child may be too young for an official “job,” but that doesn’t mean he or she is too young for other entrepreneurial endeavors. Help your child brainstorm different
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: 10, 20, 30, 40, 60, 80, 90, 120, 150, 180, 200,
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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limitations cannot be understood only through electrical specifications and nameplate data, because redundancy is included in the design. In order to obtain a thorough understanding of electromagnetic force/torque generation, one must consider thermal characteristics
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There is now firm evidence supporting the lever arm hypothesis for the origin of directional movement. Nevertheless, many pivotal issues remain. For
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as the origin, distances to the left would have negative values while the distances to right would be positive. In a perfect world, the sum of all of the moments would equal zero, indicating balanced forces across the press slide.⏎Table 1 quant
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to work side by side with humans without any physical boundaries. Also, compared to industrial robots, they are programmed to operate at lower speeds and with less ”torque strength”, making them safer to use in parallel to human workers.⏎Indeed, industrial
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
- L4:2893 excites the word 'means' after a subject
- L0:1483 weakly suppresses
- L5:102 weakly excites
- L5:1518 weakly excites
- L2:2281 weakly excites
- L0:2082 weakly excites
- L3:2026 weakly excites
- L3:2140 weakly suppresses
- L4:2434 weakly excites
- L3:877 weakly suppresses
- L4:12 weakly suppresses
- L2:2666 weakly suppresses
- L1:2583 weakly excites
- L4:2105 weakly suppresses
- L2:1566 weakly excites
- L2:1896 weakly suppresses
- L4:2825 weakly excites "to" after 'for X' infinitives
- L4:2089 weakly suppresses
- L4:2787 weakly suppresses
- L1:2843 weakly suppresses
- L2:2335 weakly suppresses
- L1:2801 weakly excites
- L5:60 weakly excites
- L1:1546 weakly excites
Feeds later layers
- L8:2053 suppresses
- L15:1167 weakly suppresses
- L9:2374 weakly excites
- L7:3064 weakly excites
- L23:1959 weakly suppresses
- L8:1922 weakly suppresses
- L7:2557 weakly suppresses
- L8:1716 weakly excites
- L10:251 weakly excites
- L10:2133 weakly excites
- L11:2761 weakly excites
- L10:2281 weakly excites
- L26:2687 weakly excites unclear: word starts like Ag and Re
- L7:1539 weakly excites
- L23:1846 weakly excites
- L7:1150 weakly excites
- L9:298 weakly excites
- L16:135 weakly excites
- L8:281 weakly suppresses
- L7:1801 weakly suppresses
- L8:2771 weakly excites
- L15:264 weakly suppresses
- L15:2550 weakly suppresses
- L7:1630 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
- tú
- 就意味着
- 체
- СП
- nero
- Trainer
- изатор
- uego
- tweeting
- trainers
Suppresses
- ays
- ld
- kinson
- Pradesh
- Cos
- licensors
- arms
- mdi
- ofs
- 支柱