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Expand Up @@ -379,7 +379,7 @@ Foundations and Trend in Information Retrieval, 2011. [The slides](https://www.f
24. Asli Celikyilmaz, Antoine Bosselut, Xiaodong He, Yejin Choi. [Deep Communicating Agents for Abstractive Summarization](https://arxiv.org/abs/1803.10357v1). arXiv:1803.10357, 2018.
25. Piji Li, Lidong Bing, Wai Lam. [Actor-Critic based Training Framework for Abstractive Summarization](https://arxiv.org/abs/1803.11070v1). arXiv:1803.11070, 2018.
26. Paul Azunre, Craig Corcoran, David Sullivan, Garrett Honke, Rebecca Ruppel, Sandeep Verma, Jonathon Morgan. [Abstractive Tabular Dataset Summarization via Knowledge Base Semantic Embeddings](https://arxiv.org/abs/1804.01503v2). arXiv:1804.01503, 2018.
27. Arman Cohan, Franck Dernoncourt, Doo Soon Kim, Trung Bui, Seokhwan Kim, Walter Chang, Nazli Goharian. [A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents](https://arxiv.org/abs/1804.05685v1). arXiv:1804.05685, 2018.
27. Arman Cohan, Franck Dernoncourt, Doo Soon Kim, Trung Bui, Seokhwan Kim, Walter Chang, Nazli Goharian. [A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents](https://arxiv.org/abs/1804.05685). arXiv:1804.05685, NAACL HLT 2018. The source code (TensorFlow, Python) and dataset are in the [long-summarization](https://github.com/armancohan/long-summarization) repo.
28. Ramakanth Pasunuru, Mohit Bansal. [Multi-Reward Reinforced Summarization with Saliency and Entailment](https://arxiv.org/abs/1804.06451v1). arXiv:1804.06451, 2018.
29. Jianmin Zhang, Jiwei Tan, Xiaojun Wan. [Towards a Neural Network Approach to Abstractive Multi-Document Summarization](https://arxiv.org/abs/1804.09010v1). arXiv:1804.09010, 2018.
30. Shuming Ma, Xu Sun, Junyang Lin, Xuancheng Ren. [A Hierarchical End-to-End Model for Jointly Improving Text Summarization and Sentiment Classification](https://arxiv.org/abs/1805.01089v2). arXiv:1805.01089v2, IJCAI 2018.
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