(Room 217-219, New Orleans, December 15, 2023, Website)
Schedule
Friday, December 15, 2023
All times are in Central Standard Time (CST) (Check local time)
Location: Room 217-219, New Orleans Convention Center (Map)
Live video stream: Link
08:55-09:00 | Introduction and Opening Remarks | |
09:00-09:30 | Invited Talk |
AI4Crypto Kristin Lauter, FAIR Labs North America, Meta |
09:30-10:00 | Invited Talk |
Exploring Mathematical Conjecturing – From Heuristic Search to Large Language Models Moa Johansson, Chalmers University |
10:00-10:30 | Invited Talk |
Axioms (and curiosity and attention) are all you need Noah D. Goodman, Stanford University |
10:30-11:00 | Break | |
11:00-12:00 | Panel Discussion |
Timothy Gowers (College de France),
Talia Ringer (UIUC),
Armando Solar-Lezama (MIT),
Yuhuai (Tony) Wu (xAI),
Mateja Jamnik (University of Cambridge)
|
12:00-13:00 | Break | |
13:00-13:15 | Contributed Talk |
Learning the Greatest Divisor - Explainable Predictions in Transformers Francois Charton, |
13:15-13:30 | Contributed Talk |
Lemur: Integrating Large Language Models in Automated Program Verification Nina Narodytska, |
13:30-13:45 | Contributed Talk |
OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text Keiran Paster, |
13:45-14:00 | Contributed Talk |
What Algorithms Can Transformers Learn? A Study in Length Generalization Hattie Zhou, |
14:00-14:30 | Invited Talk |
AI can learn from data. But can it learn to reason? Guy Van den Broeck, UCLA |
14:30-15:00 | Coffee Break | |
15:00-16:00 | Poster Session | |
16:00-16:30 | Invited Talk |
Analogical Reasoning with Large Language Models Xinyun Chen, Google DeepMind |
16:30-17:00 | Invited Talk |
Mechanisms of Symbol Processing for In-Context Learning in Transformers Paul Smolensky, JHU, Microsoft |