Discover the latest advancements in LLM research and its integration into the programming landscape. Learn about the current progress of LLMs and design the future of AI systems with principles of fairness, inclusivity, and accessibility.
Join us for a dynamic two-day workshop that merges the hands-on coding experience of hackathons with the latest in cutting-edge research presentations. Investigate the transformative potentials of generative AI at our Hackathon+Research Event, where we’ll delve into using LLMs to develop software with fair, inclusive, and accessible design.
On day 1, we’ll kick off our event with Hack FairLLM, a hackathon dedicated to exploring the potential of using LLMs to solve software development tasks. Participants will collaborate on projects under the theme of Fairness, create designs, develop technology using the latest AI models like ChatGPT, and compete for prizes! On day 2, researchers will present their current work on the development of LLMs.
This event is part of the Toward a Fair and Inclusive Future of Work with ChatGPT Emergent Data Science Program, fostering the growth of a community dedicated to the responsible development of guidelines, policies, and safeguards for the ethical use of generative AI.
January 26, 9:00 am – 5:00 pm
January 27, 9:00 am – 12:30 pm
In-person only
10th floor DSI Seminar room 10031/10032
700 University Avenue,
Toronto, ON
Hackathon
May 2, 2024
9:00 am – 5:00 pm
Research Talks
May 3, 2024
9:00 am – 12:00 pm
In-person only
DSI 10th floor Seminar Room, 700 University Avenue
Register for:
Hackathon
Research Talks
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8:30-9:00 am |
Registration and Breakfast |
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9:00-9:30 am |
Welcome and Opening |
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9:30- 12:00 pm |
Hackathon |
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12:00-1:00 pm |
Lunch |
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1:00-4:00 pm |
Hackathon |
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4:00-5:00 pm |
Demo and Result
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9:00-9:10am |
Opening |
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9:10-12:00pm |
Research Talks Does GPT Distrust Algorithms? Evaluating Large Language Models for Algorithm Aversion Jessica Bo, PhD candidate, Department of Computer Science, University of Toronto Chart What I Say: Exploring Cross-Modality Prompt Alignment in AI-Assisted Chart Authoring Ananya Bhattacharjee, PhD candidate, Department of Computer Science, University of Toronto Understanding the Role of Large Language Models in Personalizing and Scaffolding Strategies to Combat Academic Procrastination Nazar Ponochevnyi, |
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12:00-1:00pm |
Lunch |
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1:00-2:00pm |
Discussion and Closing
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