12 citations · 27 across the 7 of their papers we have counts for
7 papers
Measuring and Modeling Physical Intrinsic Motivation
Julio Martinez, Felix Binder, Haoliang Wang +3
Humans are interactive agents driven to seek out situations with interesting physical dynamics. Here we formalize the functional form of physical intrinsic motivation. We first col…
How do people incorporate advice from artificial agents when making physical judgments?
Erik Brockbank, Haoliang Wang, Justin Yang +4
How do people build up trust with artificial agents? Here, we study a key component of interpersonal trust: people's ability to evaluate the competence of another agent across repe…
Identifying concept libraries from language about object structure
Catherine Wong, William P. McCarthy, Gabriel Grand +5
Our understanding of the visual world goes beyond naming objects, encompassing our ability to parse objects into meaningful parts, attributes, and relations. In this work, we lever…
Visual resemblance and communicative context constrain the emergence of graphical conventions
Robert D. Hawkins, Megumi Sano, Noah D. Goodman +1
From photorealistic sketches to schematic diagrams, drawing provides a versatile medium for communicating about the visual world. How do images spanning such a broad range of appea…
Learning to communicate about shared procedural abstractions
William P. McCarthy, Robert D. Hawkins, Haoliang Wang +2
Many real-world tasks require agents to coordinate their behavior to achieve shared goals. Successful collaboration requires not only adopting the same communicative conventions, b…
Physion: Evaluating Physical Prediction from Vision in Humans and Machines
Daniel M. Bear, Elias Wang, Damian Mrowca +12
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,…