Maxence Pajot
@maxencepajot.bsky.social
PhD student with Stanislas Dehaene and Yair Lakretz.
I’m interested in mathematical cognition and AI
I’m interested in mathematical cognition and AI
Definitely, thanks for the suggestion!
July 17, 2025 at 8:22 AM
Definitely, thanks for the suggestion!
In short: number frequencies show consistent patterns across languages.
A simple model grounded in a Language of Thought—recursively using +, ×, and 1—captures these patterns remarkably well.
This supports the idea that number concepts are built compositionally in the mind.
doi.org/10.1016/j.co...
A simple model grounded in a Language of Thought—recursively using +, ×, and 1—captures these patterns remarkably well.
This supports the idea that number concepts are built compositionally in the mind.
doi.org/10.1016/j.co...
Redirecting
doi.org
July 15, 2025 at 4:05 PM
In short: number frequencies show consistent patterns across languages.
A simple model grounded in a Language of Thought—recursively using +, ×, and 1—captures these patterns remarkably well.
This supports the idea that number concepts are built compositionally in the mind.
doi.org/10.1016/j.co...
A simple model grounded in a Language of Thought—recursively using +, ×, and 1—captures these patterns remarkably well.
This supports the idea that number concepts are built compositionally in the mind.
doi.org/10.1016/j.co...
With the cumulative model, we get an added benefit: it yields precise hypotheses about the mental representation of each number.
For instance, 24 is most likely represented as 4×6, but also as 2×12, 3×8, or the successor of 23—in that order.
For instance, 24 is most likely represented as 4×6, but also as 2×12, 3×8, or the successor of 23—in that order.
July 15, 2025 at 4:03 PM
With the cumulative model, we get an added benefit: it yields precise hypotheses about the mental representation of each number.
For instance, 24 is most likely represented as 4×6, but also as 2×12, 3×8, or the successor of 23—in that order.
For instance, 24 is most likely represented as 4×6, but also as 2×12, 3×8, or the successor of 23—in that order.
Our model was actually missing a crucial ingredient: approximation.
Locutors experience a tradeoff between accuracy of the expressed quantity and length of the expression. Adding a parameter to account for this accurately models the whole curve.
Locutors experience a tradeoff between accuracy of the expressed quantity and length of the expression. Adding a parameter to account for this accurately models the whole curve.
July 15, 2025 at 4:03 PM
Our model was actually missing a crucial ingredient: approximation.
Locutors experience a tradeoff between accuracy of the expressed quantity and length of the expression. Adding a parameter to account for this accurately models the whole curve.
Locutors experience a tradeoff between accuracy of the expressed quantity and length of the expression. Adding a parameter to account for this accurately models the whole curve.
Fitting our models to the data, we find that both models accurately captured the downward trend as well as some local peaks, yet it failed to do so for decade numbers. Why?
July 15, 2025 at 4:02 PM
Fitting our models to the data, we find that both models accurately captured the downward trend as well as some local peaks, yet it failed to do so for decade numbers. Why?
We developed two models to explain how often a number appears:
- Shortest-path: only the simplest construction determines frequency
- Cumulative: all valid constructions contribute to frequency, weighted by their complexity
Here's how:
- Shortest-path: only the simplest construction determines frequency
- Cumulative: all valid constructions contribute to frequency, weighted by their complexity
Here's how:
July 15, 2025 at 4:02 PM
We developed two models to explain how often a number appears:
- Shortest-path: only the simplest construction determines frequency
- Cumulative: all valid constructions contribute to frequency, weighted by their complexity
Here's how:
- Shortest-path: only the simplest construction determines frequency
- Cumulative: all valid constructions contribute to frequency, weighted by their complexity
Here's how:
Building on this, we tested a new cognitive model based on a Language of Thought (LoT) introduced by Dehaene et al., 2025.
The idea: number concepts are constructed in the mind using simple building blocks—1, +, and ×.
The idea: number concepts are constructed in the mind using simple building blocks—1, +, and ×.
July 15, 2025 at 3:59 PM
Building on this, we tested a new cognitive model based on a Language of Thought (LoT) introduced by Dehaene et al., 2025.
The idea: number concepts are constructed in the mind using simple building blocks—1, +, and ×.
The idea: number concepts are constructed in the mind using simple building blocks—1, +, and ×.
Some of this isn’t new.
Dehaene & Mehler (1992) already showed that number word frequencies follow a ~1/n² law.
They suggested that while cultural or environmental factors could explain some of the frequency curve, the psychological organization of number concepts must play a major role.
Dehaene & Mehler (1992) already showed that number word frequencies follow a ~1/n² law.
They suggested that while cultural or environmental factors could explain some of the frequency curve, the psychological organization of number concepts must play a major role.
July 15, 2025 at 3:59 PM
Some of this isn’t new.
Dehaene & Mehler (1992) already showed that number word frequencies follow a ~1/n² law.
They suggested that while cultural or environmental factors could explain some of the frequency curve, the psychological organization of number concepts must play a major role.
Dehaene & Mehler (1992) already showed that number word frequencies follow a ~1/n² law.
They suggested that while cultural or environmental factors could explain some of the frequency curve, the psychological organization of number concepts must play a major role.
Using the Google N-grams database, we looked at the frequency of number words from 1 to 99 in 6 languages.
Across the board, we found two patterns:
🔻 Frequency drops with size
📈 Local spikes at certain numbers—especially round ones and those with many small divisors
Across the board, we found two patterns:
🔻 Frequency drops with size
📈 Local spikes at certain numbers—especially round ones and those with many small divisors
July 15, 2025 at 3:58 PM
Using the Google N-grams database, we looked at the frequency of number words from 1 to 99 in 6 languages.
Across the board, we found two patterns:
🔻 Frequency drops with size
📈 Local spikes at certain numbers—especially round ones and those with many small divisors
Across the board, we found two patterns:
🔻 Frequency drops with size
📈 Local spikes at certain numbers—especially round ones and those with many small divisors