Eva Portelance is an incoming Assistant Professor in the Department of Decision Sciences at HEC Montréal. Her research intersects AI and Cognitive Science. She is interested in studying how both humans and machines learn to understand language and reason about complex problems. Before joining HEC Montréal, Eva was a postdoctoral fellow at Mila – Québec AI Institute and McGill University’s NLP Group working with Timothy O’Donnell and Siva Reddy. She completed her PhD in computational/cognitive linguistics at Stanford University, co-advised by professors Dan Jurafsky and Mike C. Frank, as part of the Stanford NLP group and the Stanford Language and Cognition Lab. She is a true interdisciplinarian.
Talk
What neural networks can teach us about how we learn language | June 4
Sessions in which Eva Portelance participates
Tuesday 4 June, 2024
How can modern neural networks like large language models be useful to the field of language acquisition, and more broadly cognitive science, if they are not a priori designed to be cognitive models? As developments towards natural language understanding and generation have improved leaps and bounds, with models like GPT-4, the question of how they can inform our understanding of human language acquisition has re-emerged. This talk will try to address how AI models as objects of study can ind...