Prof. LI Ping, Department of Chinese and Bilingual Studies

Naturalistic Reading Comprehension in L1 and L2: What can “model-brain alignment” tell us about its neurocognitive mechanisms. BIRC Speakers Series and Seminars. Brain Imaging Research Center, University of Connecticut (online), 28 March 2024.

Abstract
With the rapid developments in generative AI and large language models (LLMs), researchers are assessing the impacts that these developments bring to various domains of scientific studies. In this talk, I describe the “model-brain alignment” approach that leverages the progress in LLMs. Along with recent proposals on shared computational principles in humans and machines for naturalistic comprehension (e.g., listening to stories, watching movies), we use model-brain alignment to study naturalistic reading comprehension in both native (L1) and non-native (L2) languages. By training LLM-based encoding models on brain responses to text reading, we can evaluate (a) what computational properties in the model are important to reflect human brain mechanisms in language comprehension, and (b) what model variations best reflect human individual differences during reading comprehension.