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Aug, 2019
无标注数据下的少样本对话生成:一种迁移学习方法
Few-Shot Dialogue Generation Without Annotated Data: A Transfer Learning Approach
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Igor Shalyminov, Sungjin Lee, Arash Eshghi, Oliver Lemon
TL;DR
本文介绍了一种基于 MetaLWOz 数据集的知识迁移技术,实现在少量样本下训练对话系统的方法,并在多个领域的人机对话中达到了最先进的结果,同时也不需要任何标注数据。
Abstract
Learning with minimal data is one of the key challenges in the development of practical, production-ready goal-oriented
dialogue systems
. In a real-world enterprise setting where
dialogue systems
are developed ra
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