Learning to Control the Fine-grained Sentiment for Story Ending Generation

ACL 2019 Fuli LuoDamai DaiPengcheng YangTianyu LiuBaobao ChangZhifang SuiXu Sun

Automatic story ending generation is an interesting and challenging task in natural language generation. Previous studies are mainly limited to generate coherent, reasonable and diversified story endings, and few works focus on controlling the sentiment of story endings... (read more)

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