A Bayesian framework helps address, in computational terms, what knowledge children start
with and how they construct and adapt models of the world during childhood. Within this …

In what sense does a large language model (LLM) have knowledge? We answer by
granting LLMs 'instrumental knowledge': knowledge gained by using next-word generation …

While current vision algorithms excel at many challenging tasks, it is unclear how well they
understand the physical dynamics of real-world environments. Here we introduce Physion, a …

Humans intuitively recognize objects' physical properties and predict their motion, even
when the objects are engaged in complicated interactions. The abilities to perform physical …

General physical scene understanding requires more than simply localizing and recognizing
objects--it requires knowledge that objects can have different latent properties (eg, mass or …

Many surface cues support three-dimensional shape perception, but humans can
sometimes still see shape when these features are missing—such as when an object is …

Failure to develop prospective motor control has been proposed to be a core phenotypic
marker of autism spectrum disorders (ASD). However, whether genuine differences in …

Physics perception very often faces the problem that only limited data or partial
measurements on the scene are available. In this work, we propose a strategy to learn the …

A chief goal of artificial intelligence is to build machines that think like people. Yet it has
been argued that deep neural network architectures fail to accomplish this. Researchers …

Given a visual scene, humans have strong intuitions about how a scene can evolve over
time under given actions. The intuition, often termed visual intuitive physics, is a critical …