question marks after a statement
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 responds to a question mark that comes right after a statement, often in a short rhetorical question or a heading like "Not exactly what you need?". Turning it up made the model repeat questions about itself, though that may just be a side effect of the strong push.
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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ION Exposure Attention Interpretation Exposure Exposure highlights the stimulus to which a consumer is exposed to. Exposure can be either deliberate or random. ...⏎Not exactly what you need?<|endoftext|>Allegany County’s
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% of behavioral intention, social norms are rarely even significant and always account for a very small percentage towards the variance of exercise intentions. ...⏎Not exactly what you need?<|endoftext|>Member of the Turkish National Allergy and Clinical Immunology Association. Lecturer
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Philae, to set down on the comet's surface to collect even more data, a feat never before attempted. That will certainly be worth watching.⏎Courtesy NASA?JPL-CaltechRemember last month when we posted a photo of the Earth and
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make sense. It has to describe something? Why then not just plain English(whatever language you choose)⏎String theory's mathematical
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to people seeking war with Iran – No!), this is crazy. First, he’s advocating for homosexually-active men to enter fake marriages. This is defending marriage? But even better, let’s take a quick look at Alexander’s marriage policies,
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and delayed the release? Provide reasons for your decision.⏎You must first post your answer(s) before you
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 will be a student of computer science, and I have a major project that involves developing a program to solve a problem related to the design of a neural network. I will need to be able to use the information provided in the problem,
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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lower Columbia sturgeon: not enough juveniles.⏎“Annual recruitment of sturgeon —new st<|endoftext|>Can a small camera possibly have a large lens in the front?⏎There are really "large" lenses. This search is not the biggest one,
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York, Philadelphia, Baltimore and Washington, D.C., as well as in Florida and some Southern states.⏎Don’t Hebrew Israelites have a community in southern Israel?⏎One part of the wider Black Hebrew Israelite movement began arriving in Israel in the
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and high school students)⏎- Undergraduate education: The Summer Undergraduate Research Experience (SURE) program at Washington State<|endoftext|>Is Soil A Heterogeneous Mixture?⏎Whether you’re a keen gardener already or you’re a complete beginner, understanding
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6 Printable – Maps is an crucial supply of principal information and facts for historical examination. But just what is a map? This is a deceptively simple query, before you are motivated to provide an
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
- L5:304 strongly excites
- L2:1640 excites
- L2:1566 weakly suppresses
- L2:1328 weakly excites
- L0:2587 weakly suppresses
- L5:1604 weakly excites
- L4:928 weakly suppresses
- L2:1187 weakly suppresses
- L5:1056 weakly excites
- L0:1221 weakly suppresses
- L2:1223 weakly suppresses
- L1:2836 weakly suppresses
- L3:3031 weakly suppresses
- L2:1804 weakly excites
- L4:279 weakly excites
- L1:492 weakly excites
- L2:1934 weakly suppresses
- L5:744 weakly suppresses
- L0:1968 weakly excites
- L1:2362 weakly suppresses
- L5:2384 weakly suppresses
- L2:1374 weakly suppresses
- L2:1642 weakly excites
- L1:1150 weakly suppresses
Feeds later layers
- L7:613 excites
- L11:296 weakly excites
- L16:1078 weakly excites
- L7:1806 weakly excites
- L12:1565 weakly excites
- L18:1586 weakly excites
- L7:535 weakly excites
- L9:1055 weakly excites
- L15:2531 weakly suppresses
- L18:1774 weakly excites
- L12:1921 weakly excites
- L21:868 weakly excites
- L26:2115 weakly excites
- L15:904 weakly suppresses
- L9:324 weakly suppresses
- L23:3018 weakly suppresses
- L7:1406 weakly excites
- L15:51 weakly excites
- L8:411 weakly excites
- L16:2260 weakly suppresses
- L15:2499 weakly suppresses
- L17:1480 weakly excites
- L24:402 weakly excites
- L22:203 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
- ook
- akah
- aces
- rou
- kes
- 乎
- ria
- ?
- _above
- ?
Suppresses
- scanned
- persuade
- {l
- AZE
- pair
- unst
- screened
- ยาย
- theirs
- unin