167 citations · 208 across the 5 of their papers we have counts for
8 papers
Passive Attention in Artificial Neural Networks Predicts Human Visual Selectivity
Thomas A. Langlois, H. Charles Zhao, Erin Grant +3
Developments in machine learning interpretability techniques over the past decade have provided new tools to observe the image regions that are most informative for classification…
Are Convolutional Neural Networks or Transformers more like human vision?
Shikhar Tuli, Ishita Dasgupta, Erin Grant +1
Modern machine learning models for computer vision exceed humans in accuracy on specific visual recognition tasks, notably on datasets like ImageNet. However, high accuracy can be…
Connecting Context-specific Adaptation in Humans to Meta-learning
Rachit Dubey, Erin Grant, Michael Luo +2
Cognitive control, the ability of a system to adapt to the demands of a task, is an integral part of cognition. A widely accepted fact about cognitive control is that it is context…
Universal linguistic inductive biases via meta-learning
R. Thomas McCoy, Erin Grant, Paul Smolensky +2
How do learners acquire languages from the limited data available to them? This process must involve some inductive biases - factors that affect how a learner generalizes - but it…
Reconciling meta-learning and continual learning with online mixtures of tasks
Ghassen Jerfel, Erin Grant, Thomas L. Griffiths +1
Learning-to-learn or meta-learning leverages data-driven inductive bias to increase the efficiency of learning on a novel task. This approach encounters difficulty when transfer is…
Evaluating Theory of Mind in Question Answering
Aida Nematzadeh, Kaylee Burns, Erin Grant +2
We propose a new dataset for evaluating question answering models with respect to their capacity to reason about beliefs. Our tasks are inspired by theory-of-mind experiments that…