the word 'question' referring back
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. 11 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
The neuron fires on the word 'question' when the text is pointing back to a question someone already asked, as in 'answers your question' or 'the initial question'. When it was turned up, the model's output kept circling back to answers and 'the first question', so the link to questions shows up in the steering too.
Written by Claude from this neuron's activations and steering outputs. Confidence: high. 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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't squash (compress) it at all. At KS3 and GCSE you'll be taught that you cannot compress liquids, so the the short answer to your question is yes, liquids have a definite volume :0).⏎Interested in booking a
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its climate and agriculture production. Before you go further, it is good for you to enrich your agriculture production countries here. Now, let’s get started answering your question about why Southeast Asia is the largest agricultural production region.⏎Behind the scene of becoming
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become a habit.⏎Luke 6:31 (GNBDK)⏎Do for others just what you want them to do for you.⏎To answer the original question, its seems the NT favors the LXX.⏎Of the places where the New
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volume of a lego brick⏎We will need to use the following two formulas:⏎You can now code this algorithm using Python to reveal the answer to the initial question: how many lego bricks are needed to build planet Earth!⏎Number of leg
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it is sufficient.⏎Of course the best way to see where the Ganges river is by using a map of the River Ganges.⏎I hope this answers your question Rebecca. You can find out more information on the River Ganges by looking at
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how can I determine whether two edges will be crossing? In graphs coordinates are not used, so there must be a different way than geometric to determine this.⏎For your information, the graph is implemented as a table:⏎bool adjacency_table [MAX_V
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 was reading, I was writing, and I was learning. How much I wanted to share and make something beautiful and helpful, I was writing and learning, I was sharing with a friend, I was teaching, etc. I was looking
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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0 00:10:22 CEST 2010⏎On 9/9/10 4:39 PM, Baba wrote:⏎> In below code "
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jing Xiaozhuang University, Nanjing, Jiangsu 211171, China⏎*Authors to whom correspondence should be addressed.⏎Received: 2020-8-4 / Accepted: 202
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’s study, the measure of ACO was the child’s report of how open they felt the family atmosphere was in terms of discussing adoption with their Cited by: Low self-esteem Identity issues can explain some low self-esteem, a classic adoptee
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across the country who are pushing for effective and equitable climate policies in their states. The views, thoughts, and opinions expressed in this article do not necessarily reflect those of Climate XChange.⏎Interested in submitting an article to be posted on our website?⏎
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
- L9:1541 suppresses
- L8:355 excites
- L10:1225 excites
- L7:1044 excites
- L10:1749 suppresses
- L9:1743 excites
- L6:2879 excites
- L7:61 suppresses
- L8:778 suppresses
- L8:2240 excites
- L9:1101 excites
- L10:1363 suppresses
- L10:2230 suppresses
- L10:2219 excites
- L6:1095 excites
- L9:1146 weakly excites
- L8:643 weakly excites
- L7:746 weakly excites
- L10:721 weakly suppresses
- L10:572 weakly suppresses
- L8:147 weakly excites
- L1:2389 weakly excites
- L3:147 weakly excites
- L4:443 weakly suppresses
Feeds later layers
- L13:1887 excites
- L12:2588 excites
- L16:2257 excites
- L13:148 suppresses
- L14:2498 excites
- L13:516 suppresses
- L16:2806 excites
- L15:2020 excites
- L14:1469 suppresses
- L18:1342 excites
- L17:2635 excites
- L14:2563 suppresses
- L15:826 weakly excites
- L13:1501 weakly excites
- L15:822 weakly suppresses
- L13:1942 weakly suppresses
- L14:1263 weakly excites
- L12:252 weakly excites
- L15:2008 weakly suppresses
- L21:2211 weakly excites
- L13:1594 weakly excites
- L14:377 weakly suppresses
- L17:2445 weakly excites
- L19:2179 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
- ptom
- ään
- answers
- 当之
- виз
- пунк
- pecific
- ENTION
- nage
- изатор
Suppresses
- udson
- 支架
- ティブ
- sometimes
- interrupted
- ++++++++
- yanında
- recent
- (open
- Foreign