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• W2943737083 abstract "This challenge intends to foster progress in two important aspects of dialog systems: dialog complexity and scaling to new domains. First, there is an increasing interest in building complex bots that span over multiple sub-domains to accomplish a complex user goal such as travel planning which may include hotel, restaurant, attraction and so on. To advance state-of-the-art technologies for handling complex dialogs, we over a timely task focusing on multi-domain end-to-end task completion dialog. Second, neural dialog systems require very large datasets to learn to output consistent and grammatically-correct sentences. This makes it extremely hard to scale out the system to new domains with limited in-domain data. With this challenge, our goal is to investigate whether sample complexity can decrease with time, i.e., if a dialog system that was trained on a large corpus can learn to converse about a new domain given a much smaller in-domain corpus." @default.
• W2943737083 created "2019-05-09" @default.
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• W2943737083 date "2019-03-01" @default.
• W2943737083 modified "2023-09-23" @default.
• W2943737083 title "Multi-Domain Task-Completion Dialog Challenge" @default.
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