[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]

Hi all,

Just a reminder that the CMU AI Seminar <http://www.cs.cmu.edu/~aiseminar/> is
tomorrow *12pm-1pm*:
https://cmu.zoom.us/j/93338025712?pwd=dEZvTkc0bTVtTjNkRkQzeGo5KzVZUT09.

*Noah Smith (University of Washington / AI2)* will be talking about some
latest progress in language modeling!

Thanks,
Shaojie

On Tue, Apr 6, 2021 at 2:10 PM Shaojie Bai <shaojieb at andrew.cmu.edu> wrote:

> 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)
>
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