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Language Transforms Cognition via System Alignment with Lei Yuan

Abstract: The recent rise of large language models has generated immense excitement and controversies, reigniting age-old questions within fields as broad as cognitive science, developmental psychology, neuroscience, artificial intelligence, education, and many more. What do these models "understand"? Can such distributional semantic models approximate human cognition? How can distributional semantic models be reconciled with the embodied view of human cognition in which symbols are grounded in perception, attention, bodily movement within the environment, and with other social partners? I will introduce three areas of my research program that aim to shed light on some of these issues. First, I will introduce in-lab experiments using stationary and mobile eye trackers demonstrating that language systematizes attention*: relational language guides attention and facilitates learning both in the moment and during subsequent learning. Second, I will show how data analytics methods--e.g., factor analysis, network analysis, decision trees--paired with corpora of cross-sectional and longitudinal dataset can inform crucial developmental trajectories, in which children's internal operational system incrementally transforms from bits and pieces of regularities to a more compositional-like system—*from chaos to coherence*. Lastly, I will demonstrate how DNN (Deep Neural Network) models can be used to understand *the learning of generalizable principles from limited examples and cross-linguistic variations in learning trajectories by aligning symbolic and perceptual systems. Together these studies indicate that language can transform human cognition through alignment with perceptual and action systems, with implications for "building" better biological and artificial intelligence systems. Bio: Dr. Lei Yuan is an Assistant Professor of Psychology and Neuroscience at the University of Colorado Boulder, and an affiliated faculty member at the ICS and the Computer Science Department. She is the PI of the DEL (Development, Education, and Learning) Lab ( https://www.colorado.edu/lab/del/rese.... Her research lies at the intersection of human cognition, development, education, and machine learning. Specifically, she focuses on understanding the mechanisms through which humans acquire and use various symbol systems (e.g., mathematics, language, maps, graphs), using a diverse set of methodologies including experimental and longitudinal studies, eye-tracking, training studies, and machine learning. Before Boulder, Dr. Yuan was an NIH-funded Postdoctoral Fellow at Indiana University. She earned her PhD in Cognitive Psychology from Northwestern University. ----- Watch more videos from University of Colorado Boulder Engineering & Applied Science and subscribe: https://bit.ly/37UmM5X Founded in 1893, the College of Engineering and Applied Science at the University of Colorado Boulder is the second largest of seven schools and colleges at one of the nation's top public research institutions. Join Our Community:   / cuengineering     / cuengineering     / cuengineering   Contact University of Colorado Boulder Engineering & Applied Science: https://www.colorado.edu/engineering/... #Engineering #CUBoulder #EngineeringBuff