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CIS Seminar: “Bridging Informal and Formal AI Reasoning”
February 13 at 3:30 PM - 4:30 PM
Neural language models have opened a fascinating, flexible platform for reasoning in mathematics, programming, and beyond. This talk will explore the intersection of these models and the rigor of formal reasoning. First, I discuss my work on building foundation models for mathematics and using language to guide the search for formally verified proofs. Then, I present our research on inference-time reasoning, which uncovers new scaling laws for reasoning based on optimally combining generators and verifiers. Finally, I discuss the challenge of building AI systems that improve their reasoning capabilities over time by learning from both formal and informal feedback. I close by discussing opportunities and future directions in mathematics, programming, agents, and beyond.
Sean Welleck
School of Computer Science, Carnegie Mellon University
Sean Welleck is an Assistant Professor at Carnegie Mellon University, where he leads the Machine Learning, Language, and Logic (L3) Lab. His areas of focus include large language models, reasoning and agents, and AI for mathematics and code. Sean received a Ph.D. from New York University. He was a postdoctoral scholar at the University of Washington and the Allen Institute for Artificial Intelligence. He is a recipient of a NeurIPS 2021 Outstanding Paper Award, and two NVIDIA AI Pioneering Research Awards.