For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education
April 30, 2026
This seminar covers:
• Recent progress in pretraining algorithm design for large language models (LLMs), emphasizing the role of data ordering, reasoning-centric data integration, and reinforcement-based objectives in shaping model capability.
• The introduction of a two-phase pretraining framework that formalizes strategies for data selection, blending, and sequencing
• A demonstration that front-loading reasoning-rich data during pretraining yields persistent gains in reasoning accuracy that post-training alone cannot reproduce
Follow along with the seminar schedule. Visit: https://web.stanford.edu/class/cs25/
Guest Speaker: Shrimai Prabhumoye (Mistral AI, prev. NVIDIA)
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)