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Add some papers in AAAI-2020.
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Expand Up @@ -31,6 +31,7 @@ We will keep adding papers and improving the list. Any suggestions are welcome!
* [Zhihu Dataset](https://github.com/hit-computer/MTA-LSTM) and [Composition Dataset](https://github.com/hit-computer/MTA-LSTM): Feng, Xiaocheng and Liu, Ming and Liu, Jiahao and Qin, Bing and Sun, Yibo and Liu, Ting. 2018. [Topic-to-essay generation with neural networks](https://www.ijcai.org/proceedings/2018/0567.pdf). In *Proceedings of IJCAI 2018*.
* [ACL Title and Abstract Dataset](https://github.com/EagleW/ACL_titles_abstracts_dataset): Wang, Qingyun and Zhou, Zhihao and Huang, Lifu and Whitehead, Spencer and Zhang, Boliang and Ji, Heng and Knight, Kevin. 2018. [Paper Abstract Writing through Editing Mechanism](https://aclweb.org/anthology/P18-2042). In *Proceedings of ACL 2018*.
* [AGENDA Dataset](https://github.com/rikdz/GraphWriter): Rik, Koncel-Kedziorski and Dhanush, Bekal and Yi, Luan and Mirella, Lapata and Hannaneh, Hajishirzi. 2019. [Text Generation from Knowledge Graphs with Graph Transformers](https://arxiv.org/pdf/1904.02342). In *Proceedings of NAACL-HLT 2019*.
* [Data4StylizedS2S](https://github.com/MarkWuNLP/Data4StylizedS2S): Wu, Yu and Wang, Yunli and Liu, Shujie. 2020. [A Dataset for Low-Resource Stylized Sequence-to-Sequence Generation](https://www.msra.cn/wp-content/uploads/2020/01/A-Dataset-for-Low-Resource-Stylized-Sequence-to-Sequence-Generation.pdf). In *Proceedings of AAAI 2020*.

<h2 id="tools">Tools</h2>

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* Fan, Angela and Lewis, Mike and Dauphin, Yann. 2019. [Strategies for Structuring Story Generation](https://www.aclweb.org/anthology/P19-1254). In *Proceedings of ACL 2019*.
* Wang, Liang and Zhao, Wei and Jia, Ruoyu and Li, Sujian and Liu, Jingming. 2019. [Denoising based Sequence-to-Sequence Pre-training for Text Generation](https://arxiv.org/pdf/1908.08206). In *Proceedings of EMNLP 2019*. [[code](https://github.com/yuantiku/PoDA)]
* Welleck, Sean and Kulikov, Ilia and Roller, Stephen and Dinan, Emily and Cho, Kyunghyun and Weston, Jason. 2020. [Neural Text Generation With Unlikelihood Training](https://arxiv.org/pdf/1908.04319). In *Proceedings of ICLR 2020*. [[code](https://github.com/facebookresearch/unlikelihood_training)] ([Citation](https://scholar.google.com/scholar?cites=16638535268657480159&as_sdt=2005&sciodt=0,5&hl=en): 3)
* Li, Zuchao and Wang, Rui and Chen, Kehai and Utiyama, Masso and Sumita, Eiichiro and Zhang, Zhuosheng and Zhao, Hai. 2020. [Data-dependent Gaussian Prior Objective for Language Generation](https://openreview.net/pdf?id=S1efxTVYDr). In *Proceedings of ICLR 2020*.
* Li, Zuchao and Wang, Rui and Chen, Kehai and Utiyama, Masso and Sumita, Eiichiro and Zhang, Zhuosheng and Zhao, Hai. 2020. [Data-dependent Gaussian Prior Objective for Language Generation](https://openreview.net/pdf?id=S1efxTVYDr). *Accepted by ICLR 2020*.

<h3 id="vae_based">Variational Autoencoder Based Methods</h3>

Expand Down Expand Up @@ -103,17 +104,20 @@ with Neural Networks](https://papers.nips.cc/paper/5346-sequence-to-sequence-lea
* Li, Jiwei and Monroe, Will and Shi, Tianlin and Jean, Sébastien and Ritter, Alan and Jurafsky, Dan. 2017. [Adversarial Learning for Neural Dialogue Generation](https://www.aclweb.org/anthology/D17-1230.pdf). In *Proceedings of EMNLP 2017*. [[code](https://github.com/liuyuemaicha/Adversarial-Learning-for-Neural-Dialogue-Generation-in-Tensorflow)] ([Citation](https://scholar.google.com.hk/scholar?cites=2709411320030823497&as_sdt=2005&sciodt=0,5&hl=en): 385)
* Gulrajani, Ishaan and Ahmed, Faruk and Arjovsky, Martin and Dumoulin, Vincent and Courville, Aaron C. 2017. [Improved Training of Wasserstein GANs](https://papers.nips.cc/paper/7159-improved-training-of-wasserstein-gans.pdf). In *Proceedings of NeurIPS 2017*. ([Citation](https://scholar.google.com/scholar?cites=3068694056154618633&as_sdt=2005&sciodt=0,5&hl=en): 1,102)
* Yu, Lantao and Zhang, Weinan and Wang, Jun and Yu, Yong. 2017. [SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient](https://www.aaai.org/ocs/index.php/AAAI/AAAI17/paper/download/14344/14489). In *Proceedings of AAAI 2017*. ([Citation](https://scholar.google.com/scholar?cites=13783508915327278077&as_sdt=2005&sciodt=0,5&hl=en): 436)
* Lin, Kevin and Li, Dianqi and He, Xiaodong and Zhang, Zhengyou and Sun, Ming-Ting. 2017. [Adversarial ranking for language generation](http://papers.nips.cc/paper/6908-adversarial-ranking-for-language-generation.pdf). In *Advances in NeurIPS 2017*. [[code](https://github.com/desire2020/RankGAN)] ([Citation](https://scholar.google.com/scholar?cites=6871069604642164772&as_sdt=2005&sciodt=0,5&hl=en): 117)
* Che, Tong and Li, Yanran and Zhang, Ruixiang and Hjelm, R Devon and Li, Wenjie and Song, Yangqiu and Bengio, Yoshua. 2017. [Maximum-likelihood augmented discrete generative adversarial networks](https://arxiv.org/pdf/1702.07983.pdf). *arXiv preprint arXiv:1702.07983*. [[code](https://github.com/geek-ai/Texygen)] ([Citation](https://scholar.google.com/scholar?cites=15378466307857672293&as_sdt=2005&sciodt=0,5&hl=en): 109)
* Liang, Xiaodan and Hu, Zhiting and Zhang, Hao and Gan, Chuang and Xing, Eric P. 2017. [Recurrent Topic-Transition GAN for Visual Paragraph Generation](http://openaccess.thecvf.com/content_ICCV_2017/papers/Liang_Recurrent_Topic-Transition_GAN_ICCV_2017_paper.pdf). In *Proceedings of IEEE 2017*. ([Citation](https://scholar.google.com/scholar?cites=7127182007926953895&as_sdt=2005&sciodt=0,5&hl=en): 65)
* Zhang, Yizhe and Gan, Zhe and Fan, Kai and Chen, Zhi and Henao, Ricardo and Shen, Dinghan and Carin, Lawrence. 2017. [Adversarial Feature Matching for Text Generation](https://arxiv.org/pdf/1706.03850). In *Proceedings of ICML 2017*. ([Citation](https://scholar.google.com/scholar?cites=11561684801033759674&as_sdt=2005&sciodt=0,5&hl=en): 68)
* Guo, Jiaxian and Lu, Sidi and Cai, Han and Zhang, Weinan and Yu, Yong and Wang, Jun. 2017. [Long Text Generation via Adversarial Training with Leaked Information](https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/viewPDFInterstitial/16360/16061). In *Proceedings of AAAI 2018*. ([Citation](https://scholar.google.com/scholar?cites=10032525507167574810&as_sdt=2005&sciodt=0,5&hl=en): 46)
* Guo, Jiaxian and Lu, Sidi and Cai, Han and Zhang, Weinan and Yu, Yong and Wang, Jun. 2017. [Long Text Generation via Adversarial Training with Leaked Information](https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/viewPDFInterstitial/16360/16061). In *Proceedings of AAAI 2018*. [[code](https://github.com/CR-Gjx/LeakGAN)] ([Citation](https://scholar.google.com/scholar?cites=10032525507167574810&as_sdt=2005&sciodt=0,5&hl=en): 46)
* Xu, Jingjing and Ren, Xuancheng and Lin, Junyang and Sun, Xu. 2018. [Diversity-Promoting GAN: A Cross-Entropy Based Generative Adversarial Network for Diversified Text Generation](http://www.aclweb.org/anthology/D18-1428). In *Proceedings of EMNLP 2018*. ([Citation](https://scholar.google.com/scholar?cites=7729303371257026386&as_sdt=2005&sciodt=0,5&hl=en): 2)
* Mroueh, Youssef and Li, Chun-Liang and Sercu, Tom and Raj, Anant and Cheng, Yu. 2018. [Sobolev GAN](https://arxiv.org/abs/1711.04894). In *Proceedings of ICLR 2018*. ([Citation](https://scholar.google.com/scholar?cites=16587521411741023583&as_sdt=2005&sciodt=0,5&hl=en): 22)
* Fedus, William and Goodfellow, Ian and Dai, Andrew M. 2018. [MaskGAN: Better Text Generation via Filling in the_](https://arxiv.org/pdf/1801.07736). In *Proceedings of ICLR 2018*. ([Citation](https://scholar.google.com/scholar?cites=8054442901795858629&as_sdt=2005&sciodt=0,5&hl=en): 58)
* Li, Jianing and Lan, Yanyan and Guo, Jiafeng and Xu, Jun and Cheng, Xueqi. 2019. [Differentiated Distribution Recovery for Neural Text Generation](https://www.aaai.org/ojs/index.php/AAAI/article/view/4639/4517). In *Proceedings of AAAI 2019*.
* Nie, Weili and Narodytska, Nina and Patel, Ankit. 2019. [RelGAN: Relational Generative Adversarial Networks for Text Generation](https://openreview.net/pdf?id=rJedV3R5tm). In *Proceedings of ICLR 2019*. ([Citation](https://scholar.google.com.hk/scholar?cites=8523757541722331979&as_sdt=2005&sciodt=0,5&hl=en&newwindow=1): 5)
* Chen, Francine and Chen, Yan-Ying. 2019. [Adversarial Domain Adaptation Using Artificial Titles for Abstractive Title Generation](https://www.aclweb.org/anthology/P19-1211). In *Proceedings of ACL 2019*.
* Ke, Pei and Huang, Fei and Huang, Minlie and Zhu, Xiaoyan. 2019. [ARAML: A Stable Adversarial Training Framework for Text Generation](https://arxiv.org/pdf/1908.07195v1). In *Proceedings of EMNLP 2019*. [[code]( https://github.com/kepei1106/ARAML.)]
* Zhou, Wangchunshu and Ge, Tao and Xu, Ke and Wei, Furu and Zhou, Ming. 2020. [Self-Adversarial Learning with Comparative Discrimination for Text Generation](https://openreview.net/pdf?id=B1l8L6EtDS). In *Proceedings of ICLR 2020*.
* Ke, Pei and Huang, Fei and Huang, Minlie and Zhu, Xiaoyan. 2019. [ARAML: A Stable Adversarial Training Framework for Text Generation](https://arxiv.org/pdf/1908.07195v1). In *Proceedings of EMNLP 2019*. [[code]( https://github.com/kepei1106/ARAML)]
* Zhou, Wangchunshu and Ge, Tao and Xu, Ke and Wei, Furu and Zhou, Ming. 2020. [Self-Adversarial Learning with Comparative Discrimination for Text Generation](https://arxiv.org/pdf/2001.11691.pdf). *Accepted by ICLR 2020*.
* Liu, Zhiyue and Wang, Jiahai and Liang, Zhiwei. 2020. [CatGAN: Category-aware Generative Adversarial Networks with Hierarchical Evolutionary Learning for Category Text Generation](https://arxiv.org/pdf/1911.06641). In *Proceedings of AAAI 2020*. [[code](https://github.com/williamSYSU/CatGAN)]

<h3 id="rl_based">Reinforcement Learning Based Methods</h3>

Expand All @@ -128,7 +132,8 @@ with Neural Networks](https://papers.nips.cc/paper/5346-sequence-to-sequence-lea
* Huang, Qiuyuan and Gan, Zhe and Celikyilmaz, Asli and Wu, Dapeng and Wang, Jianfeng and He, Xiaodong. 2019. [Hierarchically Structured Reinforcement Learning for Topically Coherent Visual Story Generation](https://aaai.org/ojs/index.php/AAAI/article/view/4863/4736). In *Proceedings of AAAI 2019*. ([Citation](https://scholar.google.com.hk/scholar?cites=7753557183070599302&as_sdt=2005&sciodt=0,5&hl=en&newwindow=1): 9)
* Kazuma, Hashimoto and Yoshimasa, Tsuruoka. 2019. [Accelerated Reinforcement Learning for Sentence Generation by Vocabulary Prediction](https://arxiv.org/pdf/1809.01694). In *Proceedings of NAACL-HLT 2019*.
* Chan, Hou Pong and Chen, Wang and Wang, Lu and King, Irwin. 2019. [Neural Keyphrase Generation via Reinforcement Learning with Adaptive Rewards](https://www.aclweb.org/anthology/P19-1208). In *Proceedings of ACL 2019*.
* Chen, Yu and Wu, Lingfei and Zaki, Mohammed J. 2020. [Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation](https://arxiv.org/pdf/1908.04942.pdf). [[code](https://github.com/hugochan/RL-based-Graph2Seq-for-NQG)] ([Citation](https://scholar.google.com/scholar?cites=5519507630710292821&as_sdt=2005&sciodt=0,5&hl=en): 1)
* Chen, Yu and Wu, Lingfei and Zaki, Mohammed J. 2020. [Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation](https://arxiv.org/pdf/1908.04942.pdf). *Accepted by ICLR 2020*. [[code](https://github.com/hugochan/RL-based-Graph2Seq-for-NQG)] ([Citation](https://scholar.google.com/scholar?cites=5519507630710292821&as_sdt=2005&sciodt=0,5&hl=en): 1)
* Chen, Liqun and Bai, Ke and Tao, Chenyang and Zhang, Yizhe and Wang, Guoyin and Wang, Wenlin and Henao, Ricardo and Carin, Lawrence. 2020. [Sequence Generation with Optimal-Transport-Enhanced Reinforcement Learning](https://pdfs.semanticscholar.org/826d/b2e5f340a90fc9672279f9e921b596aba4b7.pdf). In *Proceedings of AAAI 2020*.

<h3 id="kbs_based">Knowledge Based Methods</h3>

Expand All @@ -145,7 +150,8 @@ with Neural Networks](https://papers.nips.cc/paper/5346-sequence-to-sequence-lea
* Yang, Pengcheng and Luo, Fuli and Chen, Peng and Li, Lei and Chang, Baobao and Sui, Zhifang and Sun, Xu. 2019. [Knowledgeable Storyteller: A Commonsense-Driven Generative Model for Visual Storytelling](https://www.ijcai.org/proceedings/2019//0744.pdf). In *Proceedings of IJCAI 2019*.
* Yang, Pengcheng and Li, Lei and Luo, Fuli and Liu, Tianyu and Sun, Xu. 2019. [Enhancing Topic-to-Essay Generation with External Commonsense Knowledge](https://www.aclweb.org/anthology/P19-1193). In *Proceedings of ACL 2019*.
* Mao, Huanru Henry and Majumder, Bodhisattwa Prasad and McAuley, Julian and Cottrell, Garrison. 2019. [Improving Neural Story Generation by Targeted Common Sense Grounding](https://www.aclweb.org/anthology/D19-1615.pdf). In *Proceedings of EMNLP 2019*. [[code]( https://github.com/calclavia/story-generation)] ([Citation](https://scholar.google.com/scholar?cites=2364018610868616832&as_sdt=2005&sciodt=0,5&hl=en&newwindow=1): 1)
* Zhao, Xueliang and Wu, Wei and Tao, Chongyang and Xu, Can and Zhao, Dongyan and Yan, Rui. 2020. [Low-Resource Knowledge-Grounded Dialogue Generation](https://openreview.net/pdf?id=rJeIcTNtvS). In *Proceedings of ICLR 2020*.
* Zhao, Xueliang and Wu, Wei and Tao, Chongyang and Xu, Can and Zhao, Dongyan and Yan, Rui. 2020. [Low-Resource Knowledge-Grounded Dialogue Generation](https://openreview.net/pdf?id=rJeIcTNtvS). *Accepted by ICLR 2020*.
* Wang, Jian and Liu, Junhao and Bi, Wei and Liu, Xiaojiang and He, Kejing and Xu, Ruifeng and Yang, Min. 2020. [Improving Knowledge-aware Dialogue Generation via Knowledge Base Question Answering](https://arxiv.org/pdf/1912.07491). In *Proceedings of AAAI 2020*. [[code](https://github.com/siat-nlp/TransDG)]

<h3 id="style_transfer">Style Transfer</h3>

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