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Host: HKU Musketeers Foundation Institute of Data Science
Co-host: Department of Computer Science, HKU

IDS Seminar - by Prof. William Wang

Title: Principles of Reasoning: Designing Compositional and Collaborative Generative AIs

Speaker: William Wang, Mellichamp Professor of Artificial Intelligence; Director of the UCSB Center for Responsible Machine Learning

Date: Apr 18, 2024
Time: 11:00am – 12:00pm
Venue: HKU IDS Seminar Room (P603), Graduate House / Zoom

Mode: Hybrid. Seats for on-site participants are limited. A confirmation email will be sent to participants who have successfully registered. 


A majority of existing research in large language models and generative AI systems focuses on scaling and engineering. In this talk, I argue that we need a principled understanding of the science of generative AI, in particular, to understand the reasoning ability of large language models. First, I present a Bayesian latent variable approach to enhancing in-context learning in large language models (LLMs) through optimal demonstration selection, demonstrating substantial improvements across various text classification tasks. Second, I argue that modern generative AI systems must be modular and collaborative to solve complex reasoning problems. I will introduce Logic-LM, a locally grounded neuro-symbolic framework that synergizes LLMs with symbolic solvers, significantly boosting logical problem-solving abilities. We will also briefly elaborate on how to build neuro-symbolic solutions to improve the compositionality in text-to-image systems. Our observations indicate that the future of generative AI is modular and collaborative, as opposed to a single-model system.


Prof. William Wang 
Mellichamp Professor of Artificial Intelligence; Director of the Center for Responsible Machine Learning @ UC Santa Barbara

William Wang is Mellichamp Professor of Artificial Intelligence and Director of the UCSB Center for Responsible Machine Learning, UCSB Mind and Machine Intelligence Initiative, and the UCSB Natural Language Processing Group. His Ph.D. was from Carnegie Mellon University. His interests include the science of large language models and generative AIs, vision and language, neuro-symbolic reasoning, and responsible AI. He was recognized with several awards, including the Pierre-Simon Laplace Award by IEEE SPS (2024), the CRA Undergraduate Research Faculty Mentoring Award (2023), the British Computer Society – Karen Spärck Jones Award (2022), and the NSF CAREER Award in 2021. Dr. Wang was also listed among IEEE AI’s 10 to Watch in 2020 and has received accolades for his research, including the CVPR Best Student Paper Award in 2019 and the DARPA Young Faculty Award in 2018.


Professor Yi Ma
Director; Professor, Chair of Artificial Intelligence @ HKU IDS & Department of Computer Science

Professor Yi Ma is a Chair Professor in the Musketeers Foundation Institute of Data Science (HKU IDS) and Department of Computer Science at the University of Hong Kong. He took up the Directorship of HKU IDS on January 12, 2023. He is also a Professor at the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He has published about 60 journal papers, 120 conference papers, and three textbooks in computer vision, generalized principal component analysis, and high-dimensional data analysis.

Professor Ma’s research interests cover computer vision, high-dimensional data analysis, and intelligent systems. For full biography of Professor Ma, please refer to:

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