Stanford CS25: Transformers United V6 I On the Tradeoffs of State Space Models and Transformers

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education April 16, 2026 This seminar covers: • A high-level overview of a recently popular subquadratic alternative to the Transformer, the state space model (SSM) • The core characteristics and design choices of SSMs and other related modern linear models Follow along with the seminar schedule. Visit: https://web.stanford.edu/class/cs25/ Guest Speaker: Albert Gu (CMU, Cartesia AI) Instructors: • Steven Feng, Stanford Computer Science PhD student and NSERC PGS-D scholar • Karan P. Singh, Electrical Engineering PhD student and NSF Graduate Research Fellow in the Stanford Translational AI Lab • Michael C. Frank, Benjamin Scott Crocker Professor of Human Biology Director, Symbolic Systems Program • Christopher Manning, Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science, Co-Founder and Senior Fellow of the Stanford Institute for Human-Centered Artificial Intelligence (HAI)