Xiaoyan Cai
2018
A Skeleton-Based Model for Promoting Coherence Among Sentences in Narrative Story Generation
Jingjing Xu
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Xuancheng Ren
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Yi Zhang
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Qi Zeng
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Xiaoyan Cai
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Xu Sun
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
Narrative story generation is a challenging problem because it demands the generated sentences with tight semantic connections, which has not been well studied by most existing generative models. To address this problem, we propose a skeleton-based model to promote the coherence of generated stories. Different from traditional models that generate a complete sentence at a stroke, the proposed model first generates the most critical phrases, called skeleton, and then expands the skeleton to a complete and fluent sentence. The skeleton is not manually defined, but learned by a reinforcement learning method. Compared to the state-of-the-art models, our skeleton-based model can generate significantly more coherent text according to human evaluation and automatic evaluation. The G-score is improved by 20.1% in human evaluation.
2011
Simultaneous Clustering and Noise Detection for Theme-based Summarization
Xiaoyan Cai
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Renxian Zhang
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Dehong Gao
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Wenjie Li
Proceedings of 5th International Joint Conference on Natural Language Processing
2010
Simultaneous Ranking and Clustering of Sentences: A Reinforcement Approach to Multi-Document Summarization
Xiaoyan Cai
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Wenjie Li
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You Ouyang
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Hong Yan
Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010)
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Co-authors
- Wenjie Li 2
- Renxian Zhang 1
- Dehong Gao 1
- You Ouyang 1
- Hong Yan 1
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