Program
December 18th, 2025 • Wohl Conventions Center, Bar-Ilan University
Abstract
The rapid progress made over the last few years in generating linguistically coherent natural language has blurred, in the mind of many, the difference between natural language generation, understanding, knowledge retrieval and use, and the ability to reason with respect to the world.
Nevertheless, reliably and consistently supporting high-level decisions that depend on natural language understanding and heterogenous information retrieval is still difficult for fundamental reasons that range from computational complexity to data organization in the wild (and are here to stay).
I will discuss some of the challenges underlying reasoning and information access, argue that we should exploit what LLMs do well while delegating responsibility to special purpose models and solvers for decision making, and present some of our work in this space. I hope to collectively acknowledge some of the key GenAI myths and their consequences, think about their underlying causes, and discuss ways to move forward.
Bio
Dan Roth is the Chief AI Scientist at Oracle and the Eduardo D. Glandt Distinguished Professor at the University of Pennsylvania. Previously, Dan was a VP/Distinguished Scientist at AWS AI where he led the scientific effort behind Amazon’s first-generation GenAI products, including Titan Models, Amazon Q, and Amazon Bedrock. Dan is a Fellow of the AAAS, ACM, AAAI, and ACL, and a recipient of the IJCAI John McCarthy Award “for major conceptual and theoretical advances in the modeling of natural language understanding, machine learning, and reasoning.” He has published broadly in natural language processing, machine learning, knowledge representation and reasoning, and learning theory, was the Editor-in-Chief of the Journal of Artificial Intelligence Research (JAIR) and has served as a Program Chair and Conference Chair for the major conferences in his research areas. Roth has been involved in several ML/NLP/GenAI startups in domains that range from legal and compliance to health care. Dan received his B.A Summa cum laude in Mathematics from the Technion, Israel and his Ph.D. in Computer Science from Harvard University in 1995.