Common Contracts
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Distribution AgreementDistribution Agreement • April 2nd, 2019
Question answering (QA) is receiving a lot of attention over the recent years as neural network models have been consistently pushing the limit of machine comprehension to the level of human intelligence. QA is the task to challenge machines ability to understand a document and later apply the learned knowledge to answer to queries, either by completing a blank, selecting from a pool of available candidates, or pinpoint certain answer spans in the given text. Over the years, a lot of challenging and robust question answering datasets have appeared and gained a lot of interests. While numerous models have shown remarkable results with these datasets, the evidence passages, from which the answers are derived, mostly reside within wiki articles, newswire, (non-)fictional stories, or children’s books, but not from multiparty dialogue. No system has demonstrated its ability to comprehend and respond to queries in human-to-human conversations, although it is the most natural means of
