[Theory] Reminder: Talk CANCELED!!!: 1/8 Talks at TTIC (@11:30am): Siddharth Karamcheti, Stanford University
Mary Marre via Theory
theory at mailman.cs.uchicago.edu
Wed Jan 8 10:45:00 CST 2025
PLEASE NOTE: *TALK IS CANCELLED!!!*
Mary C. Marre
Faculty Administrative Support
*Toyota Technological Institute*
*6045 S. Kenwood Avenue, Rm 517*
*Chicago, IL 60637*
*773-834-1757*
*mmarre at ttic.edu <mmarre at ttic.edu>*
On Wed, Jan 8, 2025 at 8:37 AM Mary Marre <mmarre at ttic.edu> wrote:
> PLEASE NOTE: *TALK IS CANCELLED!!!*
>
> *When:* Wednesday, January 8, 2025 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=46925b13-5fd1-4f39-8654-b25a01327547>
>
>
>
>
> *Who: * Siddharth Karamcheti, Stanford University
>
>
>
> *Title: *Language-Driven Learning for Interactive Robotics
>
> *Abstract*: Building and deploying broadly capable robots requires
> systems that can efficiently learn from and work with people. To achieve
> this, robots must balance *capability* — the skills necessary to enable
> real-world deployment — and *sustainability* — the ability to grow and
> adapt through human feedback. In this talk, I will motivate *language-driven
> learning* to tackle these axes, providing robots with better abstractions
> for perception, action, and human-robot interaction. First, towards
> capability, I will present our approach for using language to learn
> flexible visual representations that can be efficiently adapted for diverse
> robotics tasks. Building on these ideas, I will then discuss and
> investigate methods for training visually-conditioned language models and
> vision-language-action policies at scale, harnessing pretrained language
> models for robust and generalizable reasoning. Finally, towards
> sustainability, I will introduce a new framework that integrates these
> foundation models to develop collaborative robots that can work alongside
> human partners, using language to express uncertainty and learn new
> behaviors from real-time interactions. I will conclude with open challenges
> for enhancing both the capability and sustainability of modern robots, with
> directions for future work.
>
> *Bio: *Siddharth Karamcheti is a final year PhD student at Stanford
> University advised by Dorsa Sadigh and Percy Liang, and a robotics intern
> at the Toyota Research Institute. His research focuses on robot learning,
> natural language processing, and human-robot interaction, with a goal of
> developing scalable approaches for human-robot collaboration. Prior to the
> PhD, he earned his bachelor’s degree in Computer Science and Literary Arts
> at Brown University, where he worked with Eugene Charniak and Stefanie
> Tellex. He is a recipient of the Open Philanthropy AI Fellowship (2018), is
> an RSS Pioneer (2024), and his research has won paper awards at conferences
> such as RSS, CoRL, ICRA, and ACL.
>
> *Host: **Matthew Walter* <mwalter at ttic.edu>
>
>
>
> Mary C. Marre
> Faculty Administrative Support
> *Toyota Technological Institute*
> *6045 S. Kenwood Avenue, Rm 517*
> *Chicago, IL 60637*
> *773-834-1757*
> *mmarre at ttic.edu <mmarre at ttic.edu>*
>
>
> On Tue, Jan 7, 2025 at 2:41 PM Mary Marre <mmarre at ttic.edu> wrote:
>
>> PLEASE NOTE: new talk time below
>>
>> *When:* Wednesday, January 8, 2025 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=46925b13-5fd1-4f39-8654-b25a01327547>
>>
>>
>>
>>
>>
>> *Who: * Siddharth Karamcheti, Stanford University
>>
>>
>>
>> *Title: *Language-Driven Learning for Interactive Robotics
>>
>> *Abstract*: Building and deploying broadly capable robots requires
>> systems that can efficiently learn from and work with people. To achieve
>> this, robots must balance *capability* — the skills necessary to enable
>> real-world deployment — and *sustainability* — the ability to grow and
>> adapt through human feedback. In this talk, I will motivate *language-driven
>> learning* to tackle these axes, providing robots with better
>> abstractions for perception, action, and human-robot interaction. First,
>> towards capability, I will present our approach for using language to learn
>> flexible visual representations that can be efficiently adapted for diverse
>> robotics tasks. Building on these ideas, I will then discuss and
>> investigate methods for training visually-conditioned language models and
>> vision-language-action policies at scale, harnessing pretrained language
>> models for robust and generalizable reasoning. Finally, towards
>> sustainability, I will introduce a new framework that integrates these
>> foundation models to develop collaborative robots that can work alongside
>> human partners, using language to express uncertainty and learn new
>> behaviors from real-time interactions. I will conclude with open challenges
>> for enhancing both the capability and sustainability of modern robots, with
>> directions for future work.
>>
>> *Bio: *Siddharth Karamcheti is a final year PhD student at Stanford
>> University advised by Dorsa Sadigh and Percy Liang, and a robotics intern
>> at the Toyota Research Institute. His research focuses on robot learning,
>> natural language processing, and human-robot interaction, with a goal of
>> developing scalable approaches for human-robot collaboration. Prior to the
>> PhD, he earned his bachelor’s degree in Computer Science and Literary Arts
>> at Brown University, where he worked with Eugene Charniak and Stefanie
>> Tellex. He is a recipient of the Open Philanthropy AI Fellowship (2018), is
>> an RSS Pioneer (2024), and his research has won paper awards at conferences
>> such as RSS, CoRL, ICRA, and ACL.
>>
>> *Host: **Matthew Walter* <mwalter at ttic.edu>
>>
>>
>>
>> Mary C. Marre
>> Faculty Administrative Support
>> *Toyota Technological Institute*
>> *6045 S. Kenwood Avenue, Rm 517*
>> *Chicago, IL 60637*
>> *773-834-1757*
>> *mmarre at ttic.edu <mmarre at ttic.edu>*
>>
>>
>> On Fri, Jan 3, 2025 at 7:18 PM Mary Marre <mmarre at ttic.edu> wrote:
>>
>>> PLEASE NOTE: new talk time below
>>>
>>> *When:* Wednesday, January 8, 2025 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=46925b13-5fd1-4f39-8654-b25a01327547>
>>>
>>>
>>>
>>>
>>>
>>> *Who: * Siddharth Karamcheti, Stanford University
>>>
>>>
>>>
>>> *Title: *Language-Driven Learning for Interactive Robotics
>>>
>>> *Abstract*: Building and deploying broadly capable robots requires
>>> systems that can efficiently learn from and work with people. To achieve
>>> this, robots must balance *capability* — the skills necessary to enable
>>> real-world deployment — and *sustainability* — the ability to grow and
>>> adapt through human feedback. In this talk, I will motivate *language-driven
>>> learning* to tackle these axes, providing robots with better
>>> abstractions for perception, action, and human-robot interaction. First,
>>> towards capability, I will present our approach for using language to learn
>>> flexible visual representations that can be efficiently adapted for diverse
>>> robotics tasks. Building on these ideas, I will then discuss and
>>> investigate methods for training visually-conditioned language models and
>>> vision-language-action policies at scale, harnessing pretrained language
>>> models for robust and generalizable reasoning. Finally, towards
>>> sustainability, I will introduce a new framework that integrates these
>>> foundation models to develop collaborative robots that can work alongside
>>> human partners, using language to express uncertainty and learn new
>>> behaviors from real-time interactions. I will conclude with open challenges
>>> for enhancing both the capability and sustainability of modern robots, with
>>> directions for future work.
>>>
>>> *Bio: *Siddharth Karamcheti is a final year PhD student at Stanford
>>> University advised by Dorsa Sadigh and Percy Liang, and a robotics intern
>>> at the Toyota Research Institute. His research focuses on robot learning,
>>> natural language processing, and human-robot interaction, with a goal of
>>> developing scalable approaches for human-robot collaboration. Prior to the
>>> PhD, he earned his bachelor’s degree in Computer Science and Literary Arts
>>> at Brown University, where he worked with Eugene Charniak and Stefanie
>>> Tellex. He is a recipient of the Open Philanthropy AI Fellowship (2018), is
>>> an RSS Pioneer (2024), and his research has won paper awards at conferences
>>> such as RSS, CoRL, ICRA, and ACL.
>>>
>>> *Host: **Matthew Walter* <mwalter at ttic.edu>
>>>
>>>
>>>
>>> Mary C. Marre
>>> Faculty Administrative Support
>>> *Toyota Technological Institute*
>>> *6045 S. Kenwood Avenue, Rm 517*
>>> *Chicago, IL 60637*
>>> *773-834-1757*
>>> *mmarre at ttic.edu <mmarre at ttic.edu>*
>>>
>>>
>>> On Fri, Jan 3, 2025 at 12:45 PM Mary Marre <mmarre at ttic.edu> wrote:
>>>
>>>> *When:* Wednesday, January 8, 2025 at* 11:00** 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=46925b13-5fd1-4f39-8654-b25a01327547>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> *Who: * Siddharth Karamcheti, Stanford University
>>>>
>>>>
>>>>
>>>> *Title: *Language-Driven Learning for Interactive Robotics
>>>>
>>>> *Abstract*: Building and deploying broadly capable robots requires
>>>> systems that can efficiently learn from and work with people. To achieve
>>>> this, robots must balance *capability* — the skills necessary to
>>>> enable real-world deployment — and *sustainability* — the ability to
>>>> grow and adapt through human feedback. In this talk, I will motivate *language-driven
>>>> learning* to tackle these axes, providing robots with better
>>>> abstractions for perception, action, and human-robot interaction. First,
>>>> towards capability, I will present our approach for using language to learn
>>>> flexible visual representations that can be efficiently adapted for diverse
>>>> robotics tasks. Building on these ideas, I will then discuss and
>>>> investigate methods for training visually-conditioned language models and
>>>> vision-language-action policies at scale, harnessing pretrained language
>>>> models for robust and generalizable reasoning. Finally, towards
>>>> sustainability, I will introduce a new framework that integrates these
>>>> foundation models to develop collaborative robots that can work alongside
>>>> human partners, using language to express uncertainty and learn new
>>>> behaviors from real-time interactions. I will conclude with open challenges
>>>> for enhancing both the capability and sustainability of modern robots, with
>>>> directions for future work.
>>>>
>>>> *Bio: *Siddharth Karamcheti is a final year PhD student at Stanford
>>>> University advised by Dorsa Sadigh and Percy Liang, and a robotics intern
>>>> at the Toyota Research Institute. His research focuses on robot learning,
>>>> natural language processing, and human-robot interaction, with a goal of
>>>> developing scalable approaches for human-robot collaboration. Prior to the
>>>> PhD, he earned his bachelor’s degree in Computer Science and Literary Arts
>>>> at Brown University, where he worked with Eugene Charniak and Stefanie
>>>> Tellex. He is a recipient of the Open Philanthropy AI Fellowship (2018), is
>>>> an RSS Pioneer (2024), and his research has won paper awards at conferences
>>>> such as RSS, CoRL, ICRA, and ACL.
>>>>
>>>> *Host: **Matthew Walter* <mwalter at ttic.edu>
>>>>
>>>>
>>>>
>>>> Mary C. Marre
>>>> Faculty Administrative Support
>>>> *Toyota Technological Institute*
>>>> *6045 S. Kenwood Avenue, Rm 517*
>>>> *Chicago, IL 60637*
>>>> *773-834-1757*
>>>> *mmarre at ttic.edu <mmarre at ttic.edu>*
>>>>
>>>
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