Ellie Pavlick is an Assistant Professor of Computer Science at Brown University. She received her PhD from University of Pennsylvania in 2017, where her focus was on paraphrasing and lexical semantics. Ellie’s research is on cognitively-inspired approaches to language acquisition, focusing on grounded language learning and on the emergence of structure (or lack thereof) in neural language models. Ellie leads the language understanding and representation (LUNAR) lab, which collaborates with Brown’s Robotics and Visual Computing labs and with the Department of Cognitive, Linguistic, and Psychological Sciences.
Talk
Symbols and Grounding in LLMs | June 14
Sessions in which Ellie Pavlick participates
Friday 14 June, 2024
Large language models (LLMs) appear to exhibit human-level abilities on a range of tasks, yet they are notoriously considered to be “black boxes”, and little is known about the internal representations and mechanisms that underlie their behavior. This talk will discuss recent work which seeks to illuminate the processing that takes place under the hood. I will focus in particular on questions related to LLM’s ability to represent abstract, compositional, and content-independent operations of ...