the word 'be' after modals
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. 17 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 reacts to the word 'be' when it comes right after a helper word like 'can', 'need to', 'going to' or 'please'. Turning it up made the model's writing wander and repeat rather than show any clear topic.
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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-term, abstract goals that may have been set by their parents (“You will become a doctor!”), but clearly defined ambitions of students themselves. So, what can be achieved with great results in school? Forget long-term goals and focus on short-term
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a job seeker who cares about the long-term sustainability of the environment, there are many things you need to be doing right now that will position you to be able to participate in the development of
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heart or blood vessel problems, such as high cholesterol or high blood pressure, a healthy lifestyle can help you manage those problems.⏎If you have children, you can be their healthy role model. If your habits are healthy, your children are more likely
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proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.⏎As the access to this document is restricted
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point.⏎Because many older people suffer from hazardous falls, having good vision is necessary to prevent them. Already having had a serious fall myself, I’m going to be very anxious to get this surgery done before my vision gets bad.⏎I urge everyone
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exercises or eating the wrong things.⏎To stop you from making mistakes at the dinner table, Bright Side has listed some of the most common diet mistakes. You could be guilty of committing some of these too!⏎1. Thinking that all calories are equal
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. I. I. I. I. I. I. I. I. I. I. I. I. I. I. I. I. I. I. I. I. I. I. I.
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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" uses 9 letters: A D E L M N O P S.⏎No direct anagrams for endoplasm found in this word list.⏎Words formed by adding one letter before or after endoplasm (in bold), or to adel
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ATRIP complex induces the Fanconi Anemia repair and Nucleotide Excision Repair (NER) pathways, as well as the p53 signaling pathway. C. Finally, a
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we don’t vote ordinary people are involved in political parties and in national/local government, they can be taken over by people who may represent a minority interest. People’s rights and freedoms are preserved by
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others can be purchased by visiting us at 111 Fairgrounds Road in Rolla, or by calling us. Low resolution images of many may be viewed by visiting the Geologic Map Index.⏎What is a geologic map?⏎Like all
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
- L16:160 weakly excites
- L16:282 weakly excites
- L16:1557 weakly suppresses 'in' meaning 'in this case' or 'in between'
- L10:29 weakly suppresses
- L15:78 weakly excites
- L14:246 weakly excites
- L0:1183 weakly suppresses
- L10:201 weakly suppresses the letter B in vitamin names
- L14:1242 weakly suppresses
- L14:570 weakly suppresses
- L16:2666 weakly excites
- L12:571 weakly excites
- L4:1319 weakly excites the 'B' in vitamin B
- L16:374 weakly excites
- L10:887 weakly suppresses the B in vitamin B names
- L16:90 weakly suppresses
- L5:203 weakly excites
- L14:251 weakly suppresses
- L16:1808 weakly suppresses
- L4:428 weakly suppresses
- L12:999 weakly excites
- L16:344 weakly suppresses
- L2:656 weakly suppresses
- L13:988 weakly excites
Feeds later layers
- L19:1001 strongly excites "be" after will or you'll
- L23:999 excites "be" after modal verbs
- L20:1540 excites
- L19:1750 suppresses
- L19:1115 suppresses
- L24:1811 suppresses
- L20:636 suppresses
- L26:1233 weakly suppresses
- L19:2033 weakly excites
- L20:1618 weakly excites 'be' after 'to' or 'need to'
- L26:1269 weakly suppresses
- L22:550 weakly excites
- L23:220 weakly suppresses
- L21:1675 weakly excites
- L23:847 weakly excites
- L19:1612 weakly excites
- L20:2254 weakly excites
- L25:546 weakly excites
- L21:935 weakly suppresses
- L27:644 weakly suppresses
- L18:960 weakly excites
- L25:1852 weakly excites
- L19:1613 weakly excites "is" after a sentence-opening "It"
- L18:1471 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
- 蝠
- 发展趋势
- Baum
- _Struct
- Carb
- friend
- ',['../
- спект
- ]=-
- utors
Suppresses
- not
- being
- seg
- probably
- -se
- 代
- 一定是
- /oauth
- oret
- own