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SUMMARY:Towards Out-of-distribution generalization in NLP - Prof. He He (N
 ew York Univeristy)
DTSTART:20220128T130000Z
DTEND:20220128T140000Z
UID:TALK169211@talks.cam.ac.uk
CONTACT:Georgi Karadzhov
DESCRIPTION:Real-world NLP models must work well when the test distributio
 n differs from the training distribution. While we have made great progres
 s in natural language understanding thanks to large-scale pre-training\, c
 urrent models still take shortcuts and rely on spurious correlations in sp
 ecific datasets. In this talk\, I will discuss the role of pre-training an
 d data in model robustness to distribution shifts. In particular\, I will 
 describe how pre-trained models avoid learning spurious correlations\, whe
 n data augmentation helps and hurts\, and how large language models can be
  leveraged to improve few-shot learning.\n\n\n%{color:red}*Please note unu
 sual time!*%\nGeorgi Karadzhov is inviting you to a scheduled Zoom meeting
 .\n\nTopic: NLIP Seminar 28.01.2022\nTime: Jan 28\, 2022 01:00 PM London\n
 \nJoin Zoom Meeting\nhttps://cl-cam-ac-uk.zoom.us/j/95639294602?pwd=SnVsK1
 BYazN5ell5VlZUM2FDVGpZQT09\n\nMeeting ID: 956 3929 4602\nPasscode: 662202\
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LOCATION:Virtual (Zoom)
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