[Colloquium] REMINDER: 10/16 TTIC Colloquium: Yejin Choi, University of Washington

[Mary Marre via Colloquium]

When:     Monday, October 16th at 11:00 a.m.

Where:    TTIC, 6045 S. Kenwood Avenue, 5th Floor, Room 526

Who:       Yejin Choi, University of Washington


Title:       From Naive Physics to Connotation: Modeling Commonsense in
Frame Semantics


Abstract: Intelligent communication requires reading between the lines,
which in turn, requires rich background knowledge about how the world
works. However, learning unspoken commonsense knowledge from language is
nontrivial, as people rarely state the obvious, e.g., ``my house is bigger
than me.’’ In this talk, I will discuss how we can recover the trivial
everyday knowledge just from language without an embodied agent. A key
insight is this: the implicit knowledge people share and assume
systematically influences the way people use language, which provides
indirect clues to reason about the world. For example, if ``Jen entered her
house’’, it must be that her house is bigger than her. In this talk, I will
first present how we can organize various aspects of commonsense — ranging
from naive physics knowledge to more pragmatic connotations — by adapting
representations of frame semantics. I will then discuss neural network
approaches that complement the frame-centric approaches. I will conclude
the talk by discussing the challenges in current models and formalisms,
pointing to avenues for future research. BIO: Yejin Choi is an associate
professor of Paul G. Allen School of Computer Science & Engineering at the
University of Washington. Her recent research focuses on integrating
language and vision, learning knowledge about the world from text and
images, modeling richer context for natural language generation, and
modeling nonliteral meaning of text using connotation frames. She was among
the IEEE’s AI Top 10 to Watch in 2015 and a co-recipient of the Marr Prize
at ICCV 2013. Her work on detecting deceptive reviews, predicting the
literary success, and learning to interpret connotation has been featured
by numerous media outlets including NBC News for New York, NPR Radio, New
York Times, and Bloomberg Business Week. She received her Ph.D. in Computer
Science at Cornell University.

Host: Kevin Gimpel <kgimpel at ttic.edu>


For more information on the colloquium series or to subscribe to the
mailing list, please see http://www.ttic.edu/colloquium.php



Mary C. Marre
Administrative Assistant
*Toyota Technological Institute*
*6045 S. Kenwood Avenue*
*Room 504*
*Chicago, IL  60637*
*p:(773) 834-1757*
*f: (773) 357-6970*
*mmarre at ttic.edu <mmarre at ttic.edu>*

On Sun, Oct 15, 2017 at 5:18 PM, Mary Marre <mmarre at ttic.edu> wrote:

> When:     Monday, October 16th at 11:00 a.m.
>
> Where:    TTIC, 6045 S. Kenwood Avenue, 5th Floor, Room 526
>
> Who:       Yejin Choi, University of Washington
>
>
> Title:       From Naive Physics to Connotation: Modeling Commonsense in
> Frame Semantics
>
>
> Abstract: Intelligent communication requires reading between the lines,
> which in turn, requires rich background knowledge about how the world
> works. However, learning unspoken commonsense knowledge from language is
> nontrivial, as people rarely state the obvious, e.g., ``my house is bigger
> than me.’’ In this talk, I will discuss how we can recover the trivial
> everyday knowledge just from language without an embodied agent. A key
> insight is this: the implicit knowledge people share and assume
> systematically influences the way people use language, which provides
> indirect clues to reason about the world. For example, if ``Jen entered her
> house’’, it must be that her house is bigger than her. In this talk, I will
> first present how we can organize various aspects of commonsense — ranging
> from naive physics knowledge to more pragmatic connotations — by adapting
> representations of frame semantics. I will then discuss neural network
> approaches that complement the frame-centric approaches. I will conclude
> the talk by discussing the challenges in current models and formalisms,
> pointing to avenues for future research. BIO: Yejin Choi is an associate
> professor of Paul G. Allen School of Computer Science & Engineering at the
> University of Washington. Her recent research focuses on integrating
> language and vision, learning knowledge about the world from text and
> images, modeling richer context for natural language generation, and
> modeling nonliteral meaning of text using connotation frames. She was among
> the IEEE’s AI Top 10 to Watch in 2015 and a co-recipient of the Marr Prize
> at ICCV 2013. Her work on detecting deceptive reviews, predicting the
> literary success, and learning to interpret connotation has been featured
> by numerous media outlets including NBC News for New York, NPR Radio, New
> York Times, and Bloomberg Business Week. She received her Ph.D. in Computer
> Science at Cornell University.
>
> Host: Kevin Gimpel <kgimpel at ttic.edu>
>
>
> For more information on the colloquium series or to subscribe to the
> mailing list, please see http://www.ttic.edu/colloquium.php
>
>
>
> Mary C. Marre
> Administrative Assistant
> *Toyota Technological Institute*
> *6045 S. Kenwood Avenue*
> *Room 504*
> *Chicago, IL  60637*
> *p:(773) 834-1757 <(773)%20834-1757>*
> *f: (773) 357-6970 <(773)%20357-6970>*
> *mmarre at ttic.edu <mmarre at ttic.edu>*
>
> On Mon, Oct 9, 2017 at 1:29 PM, Mary Marre <mmarre at ttic.edu> wrote:
>
>> When:     Monday, October 16th at 11:00 a.m.
>>
>> Where:    TTIC, 6045 S. Kenwood Avenue, 5th Floor, Room 526
>>
>> Who:       Yejin Choi, University of Washington
>>
>>
>> Title:       From Naive Physics to Connotation: Modeling Commonsense in
>> Frame Semantics
>>
>>
>> Abstract: Intelligent communication requires reading between the lines,
>> which in turn, requires rich background knowledge about how the world
>> works. However, learning unspoken commonsense knowledge from language is
>> nontrivial, as people rarely state the obvious, e.g., ``my house is bigger
>> than me.’’ In this talk, I will discuss how we can recover the trivial
>> everyday knowledge just from language without an embodied agent. A key
>> insight is this: the implicit knowledge people share and assume
>> systematically influences the way people use language, which provides
>> indirect clues to reason about the world. For example, if ``Jen entered her
>> house’’, it must be that her house is bigger than her. In this talk, I will
>> first present how we can organize various aspects of commonsense — ranging
>> from naive physics knowledge to more pragmatic connotations — by adapting
>> representations of frame semantics. I will then discuss neural network
>> approaches that complement the frame-centric approaches. I will conclude
>> the talk by discussing the challenges in current models and formalisms,
>> pointing to avenues for future research. BIO: Yejin Choi is an associate
>> professor of Paul G. Allen School of Computer Science & Engineering at the
>> University of Washington. Her recent research focuses on integrating
>> language and vision, learning knowledge about the world from text and
>> images, modeling richer context for natural language generation, and
>> modeling nonliteral meaning of text using connotation frames. She was among
>> the IEEE’s AI Top 10 to Watch in 2015 and a co-recipient of the Marr Prize
>> at ICCV 2013. Her work on detecting deceptive reviews, predicting the
>> literary success, and learning to interpret connotation has been featured
>> by numerous media outlets including NBC News for New York, NPR Radio, New
>> York Times, and Bloomberg Business Week. She received her Ph.D. in Computer
>> Science at Cornell University.
>>
>> Host: Kevin Gimpel <kgimpel at ttic.edu>
>>
>>
>> For more information on the colloquium series or to subscribe to the
>> mailing list, please see http://www.ttic.edu/colloquium.php
>>
>>
>>
>>
>> Mary C. Marre
>> Administrative Assistant
>> *Toyota Technological Institute*
>> *6045 S. Kenwood Avenue*
>> *Room 504*
>> *Chicago, IL  60637*
>> *p:(773) 834-1757 <(773)%20834-1757>*
>> *f: (773) 357-6970 <(773)%20357-6970>*
>> *mmarre at ttic.edu <mmarre at ttic.edu>*
>>
>
>
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