2.3k citations · 2.3k across the 3 of their papers we have counts for
3 papers
Learning the meanings of function words from grounded language using a visual question answering model
Eva Portelance, Michael C. Frank, Dan Jurafsky
Interpreting a seemingly-simple function word like "or", "behind", or "more" can require logical, numerical, and relational reasoning. How are such words learned by children? Prior…
The Emergence of the Shape Bias Results from Communicative Efficiency
Eva Portelance, Michael C. Frank, Dan Jurafsky +2
By the age of two, children tend to assume that new word categories are based on objects' shape, rather than their color or texture; this assumption is called the shape bias. They…
On the Opportunities and Risks of Foundation Models
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli +111
AI is undergoing a paradigm shift with the rise of models (e.g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks.…