All talks listed in Pacific Time. Schedule subject to change.

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Coffee and Check-In
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Opening Remarks
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How Do Transformers Work, Part 1

Ankur Moitra (MIT)
Video
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Break
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How Do Transformers Work, Part 2

Daniel Hsu (Columbia University)
Video
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Lunch (on your own)
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Toward Understanding In-context Learning

Tengyu Ma (Stanford University)
Video
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Reception
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Coffee and Check-In
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LLM Safety, Alignment, and Generalization

Roger Grosse (University of Toronto)
Video
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Break
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On large language models and transformers: perspectives from physics, neuroscience, and theory

Surya Ganguli (Stanford University)
Video
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Lunch
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Training Large Language Models: Practices and Research Questions

Danqi Chen (Princeton University)
Video
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Break
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Understanding and Steering Generative AI Systems

Jacob Steinhardt (UC Berkeley)
Video
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Coffee and Check-In
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Challenges in Making LLMs Safe and Robust

Aditi Raghunathan (Carnegie Mellon University)
Video
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Break
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AI Safety: Robustness, memorization, and uncertainty quantification

Tatsu Hashimoto (Stanford University)
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Lunch
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The Enigma of LLMs: on Creativity, Compositionality, Pluralism, and Paradoxes

Yejin Choi (University of Washington / NVIDIA)
Video
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Break
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Discussion Session (Danqi Chen, Yejin Choi, Daniel Hsu, Aditi Raghunathan; moderated by Umesh Vazirani)
Video