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NL Seminar Question Answering by Reasoning Across Documents with Graph Convolutional Networks
Thu, Sep 26, 2019 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Nicola De Cao, University of Amsterdam
Talk Title: Question Answering by Reasoning Across Documents with Graph Convolutional Networks
Series: Natural Language Seminar
Abstract: Most research in reading comprehension has focused on answering questions based on individual documents or even single paragraphs. We introduce a neural model which integrates and reasons relying on information spread within documents and across multiple documents. We frame it as an inference problem on a graph. Mentions of entities are nodes of this graph while edges encode relations between different mentions e.g. within and cross document co reference. Graph convolutional networks GCNs are applied to these graphs and trained to perform multi-step reasoning. Our Entity GCN method is scalable and compact, and it achieves state of the art results on a multi-document question answering dataset, WikiHo.
Biography: Nicola is a first year Ph.D. candidate at the Institute for Logic, Language and Computation ILLC at the University of Amsterdam.
He is appointed at the School of Informatics at the University of Edinburgh supervised by Prof Ivan Titov, and he is part of the Edinburgh NLP group. His work focuses on unstructured Machine Reading Comprehension also know as Question Answering.
Host: Emily Sheng
More Info: https://nlg.isi.edu/nl-seminar
Webcast: https://bluejeans.com/s/sgwNF/Location: Information Science Institute (ISI) - CR #689
WebCast Link: https://bluejeans.com/s/sgwNF/
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: https://nlg.isi.edu/nl-seminar