[CMU AI Seminar] Apr 13 at 12pm (Zoom) -- Noah Smith (U of Washington) -- Language Models: Challenges and Progress -- AI Seminar sponsored by Fortive

[Shaojie Bai]

Dear all,

We look forward to seeing you *next Tuesday (4/13)* from *1**2:00-1:00 PM
(U.S. Eastern time)* for the next talk of our *CMU AI seminar*, sponsored
by Fortive <https://careers.fortive.com/>.

To learn more about the seminar series or see the future schedule, please
visit the seminar website <http://www.cs.cmu.edu/~aiseminar/>.
<http://www.cs.cmu.edu/~aiseminar/>

On 4/13, *Noah Smith* (University of Washington / AI2) will be giving a
talk on "*Language Models: Challenges and Progress*".

*Title*: Language Models: Challenges and Progress

*Talk Abstract*: Probabilistic language models are once again foundational
to many advances in natural language processing research, bringing the
exciting opportunity to harness raw text to build language technologies.
With the emergence of deep architectures and protocols for finetuning a
pretrained language model, many NLP solutions are being cast as simple
variations on language modeling. This talk is about challenges in language
model-based NLP and some of our work toward solutions. First, we'll
consider evaluation of generated language. I'll present some alarming
findings about humans and models and make some recommendations. Second,
I'll turn to an ubiquitous design limitation in language modeling -- the
vocabulary -- and present a linguistically principled, sample-efficient
solution that enables modifying the vocabulary during finetuning and/or
deployment. Finally, I'll delve into today's most popular language modeling
architecture, the transformer, and show how its attention layers' quadratic
runtime can be made linear without affecting accuracy. Taken together, we
hope these advances will broaden the population of people who can
effectively use and contribute back to NLP.

*Speaker Bio*: Noah Smith is a Professor in the Paul G. Allen School of
Computer Science & Engineering at the University of Washington, as well as
a Senior Research Manager at the Allen Institute for Artificial
Intelligence. Previously, he was an Associate Professor of Language
Technologies and Machine Learning in the School of Computer Science at
Carnegie Mellon University. He received his Ph.D. in Computer Science from
Johns Hopkins University in 2006 and his B.S. in Computer Science and B.A.
in Linguistics from the University of Maryland in 2001. His research
interests include statistical natural language processing, machine
learning, and applications of natural language processing, especially to
the social sciences. His book, Linguistic Structure Prediction, covers many
of these topics. He has served on the editorial boards of the journals
Computational Linguistics (2009-2011), Journal of Artificial Intelligence
Research (2011-present), and Transactions of the Association for
Computational Linguistics (2012-present), as the secretary-treasurer of
SIGDAT (2012-2015 and 2018-present), and as program co-chair of ACL 2016.
Alumni of his research group, Noah's ARK, are international leaders in NLP
in academia and industry; in 2017 UW's Sounding Board team won the
inaugural Amazon Alexa Prize. He was named an ACL Fellow in 2020, "for
significant contributions to linguistic structure prediction, computational
social sciences, and improving NLP research methodology." Smith's work has
been recognized with a UW Innovation award (2016-2018), a Finmeccanica
career development chair at CMU (2011-2014), an NSF CAREER award
(2011-2016), a Hertz Foundation graduate fellowship (2001-2006), numerous
best paper nominations and awards, and coverage by NPR, BBC, CBC, New York
Times, Washington Post, and Time.

*Zoom Link*:
https://cmu.zoom.us/j/93338025712?pwd=dEZvTkc0bTVtTjNkRkQzeGo5KzVZUT09

Thanks,
Shaojie Bai (MLD)
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.srv.cs.cmu.edu/pipermail/ai-seminar-announce/attachments/20210406/29563cca/attachment.html>