Difference between revisions of "Meeting Schedule"

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'''Location:''' Hybrid - Buchanan 126, and the zoom link below
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'''Location:'''  
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* Jan 8 - Feb 5: Lucile Berkeley Buchanan Building (LBB) 430
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* Feb 12 onwards: Muenzinger D430
  
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'''Time:''' Wednesdays at 10:30am, Mountain Time
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'''Time:''' Wednesdays at 11:30am, Mountain Time
  
 
'''Zoom link:''' https://cuboulder.zoom.us/j/97014876908
 
'''Zoom link:''' https://cuboulder.zoom.us/j/97014876908
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| 01/18/23 || '''Planning, introductions, welcome!'''
 
  
 
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| 01/25/2023 || TBD
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| 01/08/2025 || Invited talk: Denis Peskoff https://denis.ai/
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'''Title''': Perspectives on Prompting
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'''Abstract''': Natural language processing is in a state of flux.  I will talk about three recent papers appearing in ACL and EMNLP conferences that are a zeitgeist of the current uncertainty of direction.  First, I will talk about a paper that evaluated the responses of large language models to domain questions.  Then, I will talk about a paper that used prompting to study the language of the Federal Reserve Board.  Last, I will discuss a new paper on identifying generated content in Wikipedia.  In addition, I will highlight a mega-paper I was involved in about prompting.
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'''Bio''': Denis Peskoff just finished a postdoc at Princeton University working with Professor Brandon Stewart.  He completed his PhD in computer science at the University of Maryland with Professor Jordan Boyd-Graber and a bachelor’s degree at the Georgetown School of Foreign Service.  His research has incorporated domain experts—leading board game players, Federal Reserve Board members, doctors, scientists—to solve natural language processing challenges.
  
 
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| 02/01/2023 || TBD
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| 01/15/2025 || '''Planning, introductions, welcome!'''
  
 
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| 02/08/2023 || TBD
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| 01/22/2025 || LSA Keynote -- Chris Potts
  
 
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| 02/15/2023 || TBD
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| 01/23/25 (Thu CS seminar) || Chenhao Tan, CS Colloquium, 3:30pm, ECCR 265
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'''Title''': Alignment Beyond Human Preferences: Use Human Goals to Guide AI towards Complementary AI
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'''Abstract''': A lot of recent work has been dedicated to guide pretrained AI with human preferences. In this talk, I argue that human preferences are often insufficient for complementing human intelligence and demonstrate the key role of human goals with two examples. First, hypothesis generation is critical for scientific discoveries. Instead of removing hallucinations, I will leverage data and labels as a guide to lead hallucination towards effective hypotheses.
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Second, I will use human perception as a guide for developing case-based explanations to support AI-assisted decision making. In both cases, faithfulness is "compromised" for achieving human goals. I will conclude with future directions towards complementary AI.
  
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'''Bio''': Chenhao Tan is an associate professor of computer science and data science at the University of Chicago, and is also a visiting scientist at Abridge. He obtained his PhD degree in the Department of Computer Science at Cornell University and bachelor's degrees in computer science and in economics from Tsinghua University. Prior to joining the University of Chicago, he was an assistant professor at the University of Colorado Boulder and a postdoc at the University of Washington. His research interests include human-centered AI, natural language processing, and computational social science. His work has been covered by many news media outlets, such as the New York Times and the Washington Post. He also won a Sloan research fellowship, an NSF CAREER award, an NSF CRII award, a Google research scholar award, research awards from Amazon, IBM, JP Morgan, and Salesforce, a Facebook fellowship, and a Yahoo! Key Scientific Challenges award.
  
 
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| 02/22/2023 || TBD
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| 01/29/25 ||  
  
 
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| 03/01/2023 || TBD
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| 02/05/25 || Bhargav's Prelim
  
 
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| 03/08/2023 || TBD
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| 02/12/25 || Michael Ginn's Prelim
  
 
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| 03/15/2023 || TBD
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| 02/19/25 || Amy's Burkhardt's Talk
  
 
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| 03/22/2023 || TBD
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| 02/26/25 || Benet's Research Talk + Someone's Else
  
 
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| 03/29/2023 || TBD
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| 03/05/25 ||  
  
 
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| 04/05/2023 || TBD
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| 03/12/25 || CLASIC Industry Day
  
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| 03/19/25 || DJ's Prelim (Late start, 12-1)
  
 
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| 04/12/2023 || TBD
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| 03/26/25 || '''No meeting - Spring Break'''
  
 
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| 04/19/2023 || TBD
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| 04/02/25 || Adam Wiemerslage's Defense
  
 
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| 04/26/2023 || TBD
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| 04/09/25 || Ali's Prelim
  
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| 04/16/25 || Elizabeth's Defense
  
 
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| 05/03/2023 || TBD
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| 04/23/25 || Maggie's Defense
  
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| 04/30/25 || NAACL, maybe no meeting?
  
 
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| 05/07/25 || Jon Cai's Defense
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|}
 
|}
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=Past Schedules=
 
=Past Schedules=
 +
* [[Fall 2024 Schedule]]
 +
* [[Spring 2024 Schedule]]
 +
* [[Fall 2023 Schedule]]
 +
* [[Spring 2023 Schedule]]
 
* [[Fall 2022 Schedule]]
 
* [[Fall 2022 Schedule]]
 
* [[Spring 2022 Schedule]]
 
* [[Spring 2022 Schedule]]

Latest revision as of 17:09, 20 January 2025

Location:

  • Jan 8 - Feb 5: Lucile Berkeley Buchanan Building (LBB) 430
  • Feb 12 onwards: Muenzinger D430

Time: Wednesdays at 11:30am, Mountain Time

Zoom link: https://cuboulder.zoom.us/j/97014876908

Date Title
01/08/2025 Invited talk: Denis Peskoff https://denis.ai/

Title: Perspectives on Prompting

Abstract: Natural language processing is in a state of flux. I will talk about three recent papers appearing in ACL and EMNLP conferences that are a zeitgeist of the current uncertainty of direction. First, I will talk about a paper that evaluated the responses of large language models to domain questions. Then, I will talk about a paper that used prompting to study the language of the Federal Reserve Board. Last, I will discuss a new paper on identifying generated content in Wikipedia. In addition, I will highlight a mega-paper I was involved in about prompting.

Bio: Denis Peskoff just finished a postdoc at Princeton University working with Professor Brandon Stewart. He completed his PhD in computer science at the University of Maryland with Professor Jordan Boyd-Graber and a bachelor’s degree at the Georgetown School of Foreign Service. His research has incorporated domain experts—leading board game players, Federal Reserve Board members, doctors, scientists—to solve natural language processing challenges.

01/15/2025 Planning, introductions, welcome!
01/22/2025 LSA Keynote -- Chris Potts
01/23/25 (Thu CS seminar) Chenhao Tan, CS Colloquium, 3:30pm, ECCR 265

Title: Alignment Beyond Human Preferences: Use Human Goals to Guide AI towards Complementary AI

Abstract: A lot of recent work has been dedicated to guide pretrained AI with human preferences. In this talk, I argue that human preferences are often insufficient for complementing human intelligence and demonstrate the key role of human goals with two examples. First, hypothesis generation is critical for scientific discoveries. Instead of removing hallucinations, I will leverage data and labels as a guide to lead hallucination towards effective hypotheses. Second, I will use human perception as a guide for developing case-based explanations to support AI-assisted decision making. In both cases, faithfulness is "compromised" for achieving human goals. I will conclude with future directions towards complementary AI.


Bio: Chenhao Tan is an associate professor of computer science and data science at the University of Chicago, and is also a visiting scientist at Abridge. He obtained his PhD degree in the Department of Computer Science at Cornell University and bachelor's degrees in computer science and in economics from Tsinghua University. Prior to joining the University of Chicago, he was an assistant professor at the University of Colorado Boulder and a postdoc at the University of Washington. His research interests include human-centered AI, natural language processing, and computational social science. His work has been covered by many news media outlets, such as the New York Times and the Washington Post. He also won a Sloan research fellowship, an NSF CAREER award, an NSF CRII award, a Google research scholar award, research awards from Amazon, IBM, JP Morgan, and Salesforce, a Facebook fellowship, and a Yahoo! Key Scientific Challenges award.

01/29/25
02/05/25 Bhargav's Prelim
02/12/25 Michael Ginn's Prelim
02/19/25 Amy's Burkhardt's Talk
02/26/25 Benet's Research Talk + Someone's Else
03/05/25
03/12/25 CLASIC Industry Day
03/19/25 DJ's Prelim (Late start, 12-1)
03/26/25 No meeting - Spring Break
04/02/25 Adam Wiemerslage's Defense
04/09/25 Ali's Prelim
04/16/25 Elizabeth's Defense
04/23/25 Maggie's Defense
04/30/25 NAACL, maybe no meeting?
05/07/25 Jon Cai's Defense


Past Schedules

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