"more" after verbs like 'find out'
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. 4 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
Fires on the word "more" in calls to action like "Find out more" or "Learn more." The effect is weak. Its strongest negative cases are the word "buffer" in technical text about Emacs markers. Turning it up gave off-topic text.
Written by Claude from this neuron's activations and steering outputs. Confidence: low. 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.
-
an invaluable guide to⏎Find out more⏎Creek Books is a⏎small publisher committed to "teaching kids to
-
like goldenrod are bumble bee magnets. So are herbs including lavendar, anise hyssop, motherwort, basil and sage.⏎Want to see more flowers -- and herbs to help bees? Check out this
-
2<|endoftext|>David Bourget (Western Ontario)⏎David Chalmers (ANU, NYU)⏎Rafael De Clercq⏎Jack Alan Reynolds⏎Learn more about PhilPapers⏎OUP Oxford (2011)⏎With more
-
, and managing some of the practical things, such as getting the right shoes or working with a personal trainer.⏎This guide’s main goal is to help you become more active, get the most from your activities, and do them safely. The key
-
track of books you want to read. Want to Read saving…. Want to Read Currently Reading Read. Other editions. Enlarge cover. Error rating book.⏎Browse more videos⏎Human Anatomy and Physiology are two most-related subjects in the field of medical
-
. It’s made to help everyone from brand new hobbyists to university Geology students, and includes an eBook, digital tools, a video tutorials. Find out more here!⏎While all obsidian meets this
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 have a lot of text in the current session, but I am not sure about the current time zone. So, how to make the current time zone and the current session have a lot? So, the answer is "current"
Most negative on
Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.
-
make-marker)) ⇒ #<marker in no buffer>⏎m1to point between the 99th and 100th characters ;; in the current buffer: (set-marker m1 1
-
00) ⇒ #<marker at 100 in markers.texi>⏎;; Now insert one character at the beginning of the buffer: (goto-char (point-min)) ⇒ 1 (insert "Q")
-
’s insertion⏎type (see Marker Insertion Types)—unless the insertion is done⏎insert-before-markers (see Insertion).⏎Insertion and deletion in a buffer must check all the markers and relocate them if necessary. This slows processing in a
-
position in that buffer. But the marker’s position value can change during the life of the marker, and often does. Insertion and deletion of text in the buffer relocate the marker. The idea is that a marker positioned between two characters remains between
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
- L3:2840 suppresses
- L3:115 suppresses
- L3:1286 excites
- L3:50 excites
- L3:464 weakly excites
- L3:63 weakly excites
- L3:59 weakly excites
- L3:1936 weakly excites
- L0:1725 weakly excites
- L3:1505 weakly suppresses
- L3:691 weakly excites
- L3:1685 weakly excites
- L2:1194 weakly suppresses
- L3:139 weakly suppresses
- L3:272 weakly excites
- L3:2439 weakly excites
- L3:1581 weakly excites "the" after "percent of" or "a lot of"
- L3:294 weakly excites
- L3:133 weakly suppresses
- L0:861 weakly suppresses
- L1:1464 weakly excites
- L2:977 weakly excites
- L3:1922 weakly suppresses
- L2:111 weakly suppresses
Feeds later layers
- L5:355 suppresses
- L20:2638 suppresses
- L5:1906 suppresses
- L6:1501 suppresses
- L5:1360 suppresses
- L21:998 suppresses
- L24:2675 suppresses
- L6:2856 suppresses
- L24:2622 suppresses
- L5:1468 weakly excites
- L8:1339 weakly suppresses
- L21:3055 weakly suppresses
- L6:2619 weakly suppresses
- L11:727 weakly excites
- L23:2267 weakly suppresses
- L9:1034 weakly suppresses
- L18:732 weakly suppresses
- L24:2550 weakly suppresses
- L21:1249 weakly suppresses
- L10:813 weakly suppresses
- L20:23 weakly excites
- L17:2339 weakly suppresses
- L5:69 weakly excites
- L18:1073 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
- elkaar
- MBER
- pheres
- Ellis
- thers
- pher
- irma
- validated
- erialize
- isContained
Suppresses
- 一个职业
- Autom
- {text
- ;text
- resume
- .GetText
- !/
- !)⏎⏎
- fullscreen
- 壁纸