27 citations · 65 across the 8 of their papers we have counts for
23 papers
Improving Systematic Generalization Through Modularity and Augmentation
Laura Ruis, Brenden Lake
Systematic generalization is the ability to combine known parts into novel meaning; an important aspect of efficient human learning, but a weakness of neural network learning. In t…
A Developmentally-Inspired Examination of Shape versus Texture Bias in Machines
Alexa R. Tartaglini, Wai Keen Vong, Brenden M. Lake
Early in development, children learn to extend novel category labels to objects with the same shape, a phenomenon known as the shape bias. Inspired by these findings, Geirhos et al…
Flexible Compositional Learning of Structured Visual Concepts
Yanli Zhou, Brenden M. Lake
Humans are highly efficient learners, with the ability to grasp the meaning of a new concept from just a few examples. Unlike popular computer vision systems, humans can flexibly l…
Fast and flexible: Human program induction in abstract reasoning tasks
Aysja Johnson, Wai Keen Vong, Brenden M. Lake +1
The Abstraction and Reasoning Corpus (ARC) is a challenging program induction dataset that was recently proposed by Chollet (2019). Here, we report the first set of results collect…
CURI: A Benchmark for Productive Concept Learning Under Uncertainty
Ramakrishna Vedantam, Arthur Szlam, Maximilian Nickel +2
Humans can learn and reason under substantial uncertainty in a space of infinitely many concepts, including structured relational concepts ("a scene with objects that have the same…
Word meaning in minds and machines
Brenden M. Lake, Gregory L. Murphy
Machines have achieved a broad and growing set of linguistic competencies, thanks to recent progress in Natural Language Processing (NLP). Psychologists have shown increasing inter…