comma ending an 'if' clause
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. 20 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 comma at the end of a sentence's opening 'If' clause, such as 'If the borrower already holds property,'. Its negative side reacts to question words that start a question, like 'What' and 'Where'. Turning it up made the model repeat question words like 'why' and 'should'.
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.
-
stress test, the borrower can make efforts to pay off their existing loans or reduce their outstanding debt before applying for a mortgage loan.⏎If the borrower already holds property, the lender will take into account their existing property and mortgage when conducting the stress test
-
the lack of specific information in the standards. If we are revising a draft of social studies standards, we should not be focusing on the cultural self-awareness of a student. I
-
draw any prehistoric scene you’d like. But the trick is that you have use the entire sheet of paper and not leave any spots blank. It sounds simple, but it can get tricky depending on what you choose to draw.⏎Here are some
-
both upper and lower case letters⏎- Use more special characters⏎- Make the way you combine them more complicated<|endoftext|>If unwed parents are going to get married, the best window of opportunity for that union seems to be before their child turns
-
caregivers provide important opportunities to observe, learn, and practice healthy, adaptive responses to adverse experiences (<|endoftext|>If you've encountered anchovies on your Caesar salad or pizza, you might wonder what kind of fish it is. Anchovies are small, shiny
-
This weakens the cell wall and it ruptures resulting in the death of the bacteria.⏎If you miss a dose of Ampicillin and are taking it regularly, take it as soon as possible. If it is almost time for your next dose
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: the idea of a single system of law, to be the very foundation of the entire economy and the public order in the entire society, and to be the only law in the entire system. The idea of a single law to be the only
Most negative on
Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.
-
I might have what?”⏎She said: “A rare disease that is called Alpha 1 Antitrypsin Deficiency.”⏎I was confused. “What? What is this? How can I cure it? What do I do?”
-
infection spread from the coffin joint, and what does it cause?⏎- axially: footrot⏎- abaxially: vertical fissure aka sand crack⏎Where are septic
-
The term butterfly effect first appeared in his 1972 paper Predictability: Does the flap of a butterfly's wings in Brazil set off a tornado in Texas?.⏎Lorenz started to develop his theories of chaos as a meteorologist
-
2016? Are they trying to avoid having to answer questions about why their flawed analysis claims the HCP is somehow better for the environment? Or why they decided not to consider a science-based alternative by the Panther Review Team? Is
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
- L18:2812 strongly excites
- L18:1586 strongly suppresses
- L17:3046 strongly suppresses answer labels and tag questions
- L15:2412 suppresses
- L13:2080 suppresses
- L19:2814 excites
- L12:1069 excites
- L17:1480 excites
- L16:2817 suppresses
- L14:1800 suppresses
- L16:1078 excites
- L11:296 suppresses
- L8:145 suppresses
- L14:441 excites
- L17:2579 suppresses
- L17:3071 excites
- L13:2701 excites
- L14:385 suppresses
- L6:1572 suppresses
- L5:1800 suppresses
- L17:2638 suppresses
- L13:2939 excites
- L15:1655 excites
- L15:2327 suppresses
Feeds later layers
- L21:728 strongly excites
- L27:656 strongly excites
- L21:1362 strongly excites
- L25:576 strongly excites
- L24:1439 strongly excites
- L21:1538 excites
- L22:2765 excites
- L23:594 excites
- L22:1414 excites
- L24:2138 excites comma before 'right?' tag
- L24:402 excites
- L23:320 excites
- L26:1046 excites
- L26:1836 excites
- L22:1933 excites
- L26:613 excites
- L21:262 suppresses
- L27:960 excites
- L26:1185 excites
- L25:962 excites
- L26:1097 excites
- L23:873 excites unclear: document ends and math commas
- L22:543 excites
- L21:2363 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
- 是否会
- how
- 会不会
- 是否
- why
- 有没有
- 是不是
- 是怎么
- 是否
- 是什么
Suppresses
- lessly
- ollower
- lastic
- ifiers
- eland
- ankan
- 绎
- conomy
- 鞭
- prung