Learning with Graphs in Natural Language Generation and Relation Extraction

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• Zhijiang Guo (University of Cambridge)
• Friday 29 January 2021, 12:00-13:00
• Virtual (Zoom).

If you have a question about this talk, please contact James Thorne.

Join Zoom Meeting https://cl-cam-ac-uk.zoom.us/j/97072620010?pwd=clNrblR6MDh0SFgzYzZDTXlMMHluQT09

Meeting ID: 970 7262 0010 Passcode: 126902

Graph is a ubiquitous structure in natural language processing (NLP), which describes a collection of entities, represented as nodes, and their pairwise relationships, represented as edges. Many sentence-level meaning representations employ directed, acyclic graphs as the underlying formalism, while most tree-based syntactic representations can also be regarded as graphs. In this talk, we mainly focus on integrating graphs for downstream tasks, such as natural language generation and relation extraction.

This talk is part of the NLIP Seminar Series series.

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