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SUMMARY:Learning with Graphs in Natural Language Generation and Relation E
 xtraction - Zhijiang Guo (University of Cambridge)
DTSTART:20210129T120000Z
DTEND:20210129T130000Z
UID:TALK156106@talks.cam.ac.uk
CONTACT:James Thorne
DESCRIPTION:Join Zoom Meeting\nhttps://cl-cam-ac-uk.zoom.us/j/97072620010?
 pwd=clNrblR6MDh0SFgzYzZDTXlMMHluQT09\n\nMeeting ID: 970 7262 0010\nPasscod
 e: 126902\n\nGraph is a ubiquitous structure in natural language processin
 g (NLP)\, which describes a collection of entities\, represented as nodes\
 , and their pairwise relationships\, represented as edges. Many sentence-l
 evel meaning representations employ directed\, acyclic graphs as the under
 lying formalism\, while most tree-based syntactic representations can also
  be regarded as graphs. In this talk\, we mainly focus on integrating grap
 hs for downstream tasks\, such as natural language generation and relation
  extraction. 
LOCATION:Virtual (Zoom)
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