[Theory] TODAY: 5/12 TTIC Distinguished Lecture Series: Richard Zemel, Columbia University

[Brandie Jones via Theory]

*When:    * Monday, May 12th at *11:30 AM CT*



*Where:    *Talk will be given *live, in-person* at

                     TTIC, 6045 S. Kenwood Avenue

                     5th Floor, Room 530


*Virtually:  *via Panopto (Livestream
<https://uchicago.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=bc9cc75b-866b-4915-a52a-b2480121118b>
)



*Who:         *Richard Zemel, Columbia University


*Title:        *Improving the Diversity and Evaluation of Large Models

*Abstract: *Given their increasing ubiquity it is of the utmost importance
to ensure that AI systems can represent a diverse set of human values and
perspectives. Meanwhile progress on this type of control of Large Language
Models (LLMs) has been hampered by a fundamental underlying problem in
generative models: the difficulty of evaluating their behavior. With their
enormous range of inputs and responses and the wide variety of intended
applications and dimensions along which to judge the responses, evaluation
is extremely challenging.  I will describe two strands of research to help
address these needs.

The first aims to develop approaches that permit reliable and fine-grained
control over LLM generations, which allow them to be steered towards a
broad set of viewpoints. The second aims to rigorously combine
model-generated labels of an LLM's responses with a small pool of
ground-truth labels, to allow estimates of different aspects of the range
of responses. I will describe quantitative and qualitative evaluations of
these methods on a number of benchmark datasets, spanning public opinion
data, educational tutoring, economic disparities, and LLM toxicity and
summarization quality.

*Bio:*  Richard Zemel is the Trianthe Dakolias Professor of Engineering and
Applied Science in the Computer Science Department at Columbia University.
He is the Director of the NSF AI Institute for Artificial and Natural
Intelligence (ARNI). He was the Co-Founder and inaugural Research Director
of the Vector Institute for Artificial Intelligence. He is a Canadian
Institute for Advanced Research AI Chair, an Amazon Scholar, and is on the
Advisory Board of the Neural Information Processing Society.  His research
contributions include foundational work on systems that learn useful
representations of data with little or no supervision; graph-based machine
learning; and algorithms for fair and robust machine learning.

Hos*t: Avrim Blum <avrim at ttic.edu>*


--
*Brandie Jones *
*Executive **Administrative Assistant*
Toyota Technological Institute
6045 S. Kenwood Avenue
Chicago, IL  60637
www.ttic.edu
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