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Coffee and Check-In
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LLM Reasoning
Denny Zhou (Google DeepMind)
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Break
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The Key Ingredients of Optimizing Test-Time Compute and What's Still Missing
Aviral Kumar (Carnegie Mellon University)
–
Lunch (on your own)
–
Talk by
Georgios-Alex Dimakis (UC Berkeley)
–
Break
–
Efficient Policy Optimization Techniques for LLMs
Kianté Brantley (Harvard University)
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Talk by
Sewon Min (UC Berkeley)
–
Coffee and Check-In
–
Talk by
Yoon Kim (Massachusetts Institute of Technology)
–
Break
–
Reducing the Dimension of Language: A Spectral Perspective on Transformers
Elad Hazan (Princeton University)
–
Lunch (on your own)
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Mixed-modal Language Modeling: Chameleon, Transfusion, and Mixture of Transformers
Luke Zettlemoyer (University of Washington)
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Break
–
Liquid Networks
Daniela Rus (MIT)
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Panel Discussion
–
Coffee and Check-In
–
Inference Scaling: A New Frontier for AI Capability
Azalia Mirhoseini (Stanford / DeepMind)
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Break
–
Talk by
Zaid Harchaoui (University of Washington)
–
Lunch (on your own)
–
Talk by
Danqi Chen (Princeton University)
–
Break
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Talk by
Siva Reddy (IVADO - Mila - McGill University)
–
Coffee and Check-In
–
Advancing Diffusion Models for Text Generation
Kilian Weinberger (Cornell University)
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Break
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Controllable and Creative Natural Language Generation
Nanyun (Violet) Peng (UCLA)
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Lunch (on your own)
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Transformers can learn compositional function
Jason Lee (Princeton University)
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Break
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Predicting and optimizing the behavior of large ML models
Andrew Ilyas (Stanford University)
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Panel Discussion
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Coffee and Check-In
–
Towards sequence-to-sequence models without activation functions
Grigorios Chrysos (University of Wisconsin-Madison)
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Break
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Context-enhanced learning and skill-based learning (rough topic)
Sanjeev Arora (Princeton University)
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Lunch (on your own)
–
Talk by
Guilaume Lajoie (Univeristy of Monteal)
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Break
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Talk by
Swabha Swayamdipta (University of Southern California)
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