Stanford CS25: Transformers United V6 I Overview of Transformers - YouTube
Hazel Nam and Lucas Amard explore Joint Embedding Predictive Architectures (JEPA) for world modeling. The discussion focuses on enhancing object-centric representation learning and dynamics, proposing simplified training methods like Causal JEPA and LeWorldModel to improve interaction understanding and control in complex environments.
For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education April 2, 2026 This seminar covers: • Overview of the history of ML/NLP, Transformers, and how they work • Recent trends, breakthroughs, applications, and current challenges Follow along with the seminar schedule. Visit: https://web.stanford.edu/class/cs25/ 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…
saved by
related reading
- Stanford CS25: Transformers United V6 I From Representation Learning to World Modelingyoutube.com
- Stanford CS25: Transformers United V6 I Serving Transformers: Lessons from the Trenchesyoutube.com
- Next-Latent Prediction Transformers Learn World Models feat. Jayden Teoh from MITyoutube.com
- RLMs are Compositional Generalizers with Alex Zhang from MITyoutube.com
- Recursive Language Models — Alex Zhang, MIT PhDyoutube.com
- Everything About Transformerskrupadave.com
- Transformers Laid Outgoyalpramod.github.io
- The Illustrated Transformer – Jay Alammar – Visualizing machine learning one concept at a time.jalammar.github.io
- A Mathematical Framework for Transformer Circuitstransformer-circuits.pub
- Transformers from Scratche2eml.school
- Transformer Explainer: LLM Transformer Model Visually Explainedpoloclub.github.io
- A Conceptual Guide to Transformers: Part Ibenlevinstein.substack.com