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We propose a method for controlled narrative/story generation where we are able to guide the model to produce coherent narratives with user-specified target endings by interpolation: for example, we are told that Jim went hiking and at the end Jim needed to be rescued, and we want the model to incrementally generate steps along the way.
RoBERTa: A Robustly Optimized BERT Pretraining Approach
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Logic and conversation
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A Knowledge-Enhanced Pretraining Model for Commonsense Story Generation
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Angela Fan, Mike Lewis, and Yann Dauphin. 2019 · 2019
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Jian Guan, Fei Huang, Zhihao Zhao, Xiaoyan Zhu, and Minlie Huang. 2020 · 2020
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