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SUMMARY:From Translation Divergences to Structure-aware Neural Machine Tra
 nslation - Omri Abend\, The Hebrew University of Jerusalem
DTSTART:20210204T110000Z
DTEND:20210204T120000Z
UID:TALK157051@talks.cam.ac.uk
CONTACT:Marinela Parovic
DESCRIPTION:Languages present a wide range of structures for expressing si
 milar\nmeanings. This variation has historically motivated the integration
  of\nlinguistic structure into machine translation (MT) models\, so as to\
 nabstract away from realization differences\, but such integration has\nbe
 en receiving less attention since the introduction of neural MT\nmodels. I
 n my talk I will discuss ongoing work we’re carrying out in\nthe lab\, o
 n characterizing divergences and their impact on the\nperformance in today
 ’s neural MT models\, as well as on two approaches\nfor integrating synt
 actic structure into MT models to address this\ngap.\n\nJoint work with ma
 ny lab members and collaborators\, notably Leshem\nChoshen\, Dmitry Nikola
 ev\, Asaf Yehudai and Lior Fox.
LOCATION:https://cam-ac-uk.zoom.us/j/97599459216?pwd=QTRsOWZCOXRTREVnbTJBd
 XVpOXFvdz09
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