Program

May 11, 2024 (CET)

Start   End   Description In-person Virtual
09:00   09:15    Introduction and Opening :white_check_mark: :white_check_mark:
09:15   10:00    Keynote 1: James Zou (Stanford U) - Data scaling laws and data attribution for generative AI :white_check_mark: :white_check_mark:
10:00   10:35    Invited Talk 1: Abdulmotaleb El Saddik (U Ottawa) :white_check_mark: :white_check_mark:
10:35   11:00    Coffee break / networking break :white_check_mark:  
11:00   12:00    Panel 1: Data 2024: What are the important research questions for the DMLR community in light of foundation models? :white_check_mark: :white_check_mark:
12:00   1:00    Lunch Break :white_check_mark:  
1:00   1:45    Keynote 2: Baharan Mirzasoleiman (UCLA) - Efficient Pre-training on Massive Datasets: A Data Perspective :white_check_mark: :white_check_mark:
1:45   2:20    Invited Talk 1: Chelsea Finn (Stanford U)   :white_check_mark:
2:20   2:45    Coffee break / networking break :white_check_mark:  
2:45   3:15    Announcements :white_check_mark:  
          - DataPerf & Dynabench    
          - Challenge results    
          - AI for Good    
          - Update on DMLR Journal    
          - Croissant data format    
          - Common Crawl    
3:15   4:15    Panel 2: Generative AI for Good: What are the savior applications of generative AI and what data needs do they have? :white_check_mark: :white_check_mark:
4:15   5:15    Poster session :white_check_mark:  
5:15   5:30    Concluding Remarks :white_check_mark: :white_check_mark:
7:00   9:00    Post-workshop social event :white_check_mark: