Stanford CS25: Transformers United V6 I From Next-Token Prediction to Next-Generation Intelligence @stanfordonline
Stanford CS25: Transformers United V6 I From Next-Token Prediction to Next-Generation Intelligence  @stanfordonline
Uploaded May 2026 | Updated September 2026, 2 weeks ago
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)
Stanford CS25: Transformers United V6 I From Next-Token Prediction to Next-Generation IntelligenceStanford CS221 | Autumn 2025 | Lecture 12: Bayesian Networks IStanford CS221 | Autumn 2025 | Lecture 5: Search IStanford CS229 Machine Learning | Spring 2026 | Lecture 7: Neural Networks 1 (Architecture)Stanford CS153 Frontier Systems | The Road Ahead: Resilience RequiredNew Stanford Course: Agentic AIOverview: Business Opportunities and Applications of Generative AIStanford CS229 Machine Learning | Spring 2026 | Lecture 16: Basic Concept in RL, Policy GradientStanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 7: Dynamic ProgrammingStanford CME296 Diffusion & Large Vision Models | Spring 2026 | Lecture 7 - EvaluationOur Learners share about their experience in the Engineering Leadership ProgramStanford CS336 Language Modeling from Scratch | Spring 2026 | Lecture 5: GPUs, TPUs
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Stanford CS25: Transformers United V6 I From Next-Token Prediction to Next-Generation Intelligence

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