- Interactive Dual Generative Adversarial Networks for Image Captioning, Junhao Liu (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences); Kai Wang (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences); Chunpu Xu (Huazhong University of Science and Technology); Zhou Zhao (Zhejiang University); Ruifeng Xu (Harbin Institute of Technology (Shenzhen)); Ying Shen (Peking University Shenzhen Graduate School); Min Yang ( Chinese Academy of Sciences).
- Revision in Continuous Space: Unsupervised Text Style Transfer without Adversarial Learning, Dayiheng Liu (Sichuan University); Jie Fu (Mila, Polytechnique Montreal); Yidan Zhang (Sichuan University); Chris Pal (MILA, Polytechnique Montréal, Element AI); Jiancheng Lv (Sichuan University).
- CatGAN: Category-aware Generative Adversarial Networks with Hierarchical Evolutionary Learning for Category Text Generation, Zhiyue Liu (Sun Yat-sen University); Jiahai Wang (Sun Yat-sen University); Zhiwei Liang (Sun Yat-sen University).
- Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples, Minhao Cheng (UCLA); Jinfeng Yi (JD AI Research); Pin-Yu Chen (IBM Research); Huan Zhang (UCLA); Cho-Jui Hsieh (UCLA).
- Posterior-GAN: Towards Informative and Coherent Response Generation with Posterior Generative Adversarial Network, Shaoxiong Feng (Beijing Institute of Technology); Hongshen Chen (JD.com); Kan Li (Beijing Insitiute of Technology, China); Dawei Yin (JD.com).
- Meta-CoTGAN: A Meta Cooperative Training Paradigm for Improving Adversarial Text Generation, Haiyan Yin (Baidu Research); Dingcheng Li (Baidu Research); XU LI (Baidu Research); Ping Li (Baidu).
- Adversarial Oracular Seq2seq Learning for Sequential Recommendation, Pengyu Zhao, Tianxiao Shui, Yuanxing Zhang, Kecheng Xiao, Kaigui Bian.
- Adaptively Multi-Objective Adversarial Training for Dialogue Generation, Xuemiao Zhang, Zhouxing Tan, Xiaoning Zhang, Yang Cao, Rui Yan.
- Argot: Generating Adversarial Readable Chinese Texts, Zihan Zhang, Mingxuan Liu, Chao Zhang, Yiming Zhang, Zhou Li, Qi Li, Haixin Duan, Donghong Sun.
- A Reinforced Generation of Adversarial Examples for Neural Machine Translation, Wei Zou, Shujian Huang, Jun Xie, Xinyu Dai and Jiajun Chen.
- AdvAug: Robust Adversarial Augmentation for Neural Machine Translation, Yong Cheng, Lu Jiang, Wolfgang Macherey and Jacob Eisenstein.
- DeSePtion: Dual Sequence Prediction and Adversarial Examples for Improved Fact-Checking, Christopher Hidey, Tuhin Chakrabarty, Tariq Alhindi, Siddharth Varia, Kriste Krstovski, Mona Diab and Smaranda Muresan.
- Improving Adversarial Text Generation by Modeling the Distant Future, Ruiyi Zhang, Changyou Chen, Zhe Gan, Wenlin Wang, Dinghan Shen, Guoyin Wang, Zheng Wen and Lawrence Carin.
- Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations, Oana-Maria Camburu, Brendan Shillingford, Pasquale Minervini, Thomas Lukasiewicz and Phil Blunsom.
- A Geometry-Inspired Attack for Generating Natural Language Adversarial Examples, Zhao Meng and Roger Wattenhofer.
- Sequential Recommendation with Self-attentive Multi-adversarial Network, Ruiyang Ren: Renmin University of China; Zhaoyang Liu: Alibaba Group; Yaliang Li: Alibaba Group; Wayne Xin Zhao: Renmin University of China; Hui Wang: Renmin University of China; Bolin Ding: Alibaba Group; Ji-Rong Wen: Renmin University of China.
- Coding Electronic Health Records with Adversarial Reinforcement Path Generation, Shanshan Wang: Shandong University; Pengjie Ren: University of Amsterdam; Zhumin Chen: Shandong University; Zhaochun Ren: Shandong University; Jian-Yun Nie: Université de Montréal; Jun Ma: Shandong University; Maarten de Rijke: University of Amsterdam.
- Leveraging Adversarial Training in Self-Learning for Cross-Lingual Text Classification, Xin Dong: Rutgers University; Yaxin Zhu: Rutgers University; Yupeng Zhang: Rutgers University; Zuohui Fu: Rutgers University; Dongkuan Xu: The Pennsylvania State University; Sen Yang: Linkedin; Gerard de Melo: Rutgers University.
- Sequential-based Adversarial Optimisation for Personalised Top-N Item Recommendation, Jarana Manotumruksa: University College London; Emine Yilmaz: University College London.
- Self-Adversarial Learning with Comparative Discrimination for Text Generation, Wangchunshu Zhou, Tao Ge, Ke Xu, Furu Wei, Ming Zhou.
- Language GANs Falling Short, Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin.
- Discriminative Adversarial Search for Abstractive Summarization, Thomas Scialom (reciTAL) · Paul-Alexis Dray (reciTAL) · Sylvain Lamprier (LIP6 - Sorbonne Universités) · Benjamin Piwowarski (Sorbonne Université) · Jacopo Staiano (reciTAL).
- Adversarial Mutual Information for Text Generation, Boyuan Pan (Zhejiang University) · Yazheng Yang (Zhejiang University) · Kaizhao Liang (University of Illinois, Urbana Champaign) · Bhavya Kailkhura (LLNL) · Zhongming Jin (Alibaba Group) · Xian-Sheng Hua (Alibaba Group) · Deng Cai (ZJU) · Bo Li (UIUC).
- Improving Image Captioning with Conditional Generative Adversarial Nets, CHEN CHEN (Tencent); SHUAI MU (Tencent); WANPENG XIAO (Tencent); ZEXIONG YE (Tencent); LIESI WU (Tencent); QI JU (Tencent).
- Parallel Wasserstein Generative Adversarial Nets with Multiple Discriminators, Yuxin Su, Shenglin Zhao, Xixian Chen, Irwin King, Michael R. Lyu.
- Learning to Draw Text in Natural Images with Conditional Adversarial Networks, Shancheng Fang, Hongtao Xie, Jianjun Chen, Jianlong Tan, Yongdong Zhang.
- Open-Domain Why-Question Answering with Adversarial Learning to Encode Answer Texts, Jong-Hoon Oh, Kazuma Kadowaki, Julien Kloetzer, Ryu Iida and Kentaro Torisawa.
- Adversarial Domain Adaptation Using Artificial Titles for Abstractive Title Generation, Francine Chen and Yan-Ying Chen.
- Effective Adversarial Regularization for Neural Machine Translation, Motoki Sato, Jun Suzuki and Shun Kiyono.
- Generating Fluent Adversarial Examples for Natural Languages, Huangzhao Zhang, Hao Zhou, Ning Miao and Lei Li.
- Generating Natural Language Adversarial Examples through Probability Weighted Word Saliency, Shuhuai Ren, Yihe Deng, Kun He and Wanxiang Che.
- Retrieval-Enhanced Adversarial Training for Neural Response Generation, Qingfu Zhu, Lei Cui, Wei-Nan Zhang, Furu Wei and Ting Liu.
- Robust Neural Machine Translation with Doubly Adversarial Inputs, Yong Cheng, Lu Jiang and Wolfgang Macherey.
- ARAML: A Stable Adversarial Training Framework for Text Generation, Pei Ke, Fei Huang, Minlie Huang and xiaoyan zhu.
- Multiple Text Style Transfer by using Word-level Conditional Generative Adversarial Network with Two-Phase Training, Chih-Te Lai, Yi-Te Hong, Hong-You Chen, Chi-Jen Lu and Shou-De Lin.
- Pun-GAN: Generative Adversarial Network for Pun Generation, Fuli Luo, Shunyao Li, Pengcheng Yang, Lei Li, Baobao Chang, Zhifang Sui and Xu SUN.
- Latent Code and Text-based Generative Adversarial Networks for Soft-text Generation, Md Akmal Haidar, Mehdi Rezagholizadeh, Alan Do Omri and Ahmad Rashid.
- On Evaluation of Adversarial Perturbations for Sequence-to-Sequence Models, Paul Michel, Xian Li, Graham Neubig and Juan Pino.
- Multi-Modal Generative Adversarial Network for Short Product Title Generation in Mobile E-Commerce, Jianguo Zhang, Pengcheng Zou, Zhao Li, Yao Wan, Xiuming Pan, Yu Gong and Philip S. Yu.
- Answer-based Adversarial Training for Generating Clarification Questions, Sudha Rao and Hal Daumé III
- Evaluating Text GANs as Language Models, Guy Tevet, Gavriel Habib, Vered Shwartz and Jonathan Berant.
- Towards Robust and Discriminative Sequential Data Learning: When and How to Perform Adversarial Training? Xiaowei Jia (University of Minnesota);Sheng Li (University of Georgia);Handong Zhao (Adobe);Sungchul Kim (Adobe);Vipin Kumar (University of Minnesota).
- EnsembleGAN: Adversarial Learning for Retrieval-Generation Ensemble Model on Short-Text Conversation, Jiayi Zhang, Chongyang Tao, Zhenjing Xu, Qiaojing Xie, Wei Chen and Rui Yan.
- BoFGAN: Towards A New Structure of Backward-or-Forward Generative Adversarial Nets, M.K.Sophie Chen (Peking University, China); Xinyi Lin (Peking University, China); Chen Wei (Turing Robot, China); Rui Yan (Peking University, China).
- MisGAN: Learning from Incomplete Data with Generative Adversarial Networks, Steven Cheng-Xian Li, Bo Jiang, Benjamin Marlin.
- RelGAN: Relational Generative Adversarial Networks for Text Generation, Weili Nie, Nina Narodytska, Ankit Patel.
- Improving Neural Language Modeling via Adversarial Training, Dilin Wang, Chengyue Gong, Qiang Liu.
- Training Language GANs from Scratch, Cyprien de Masson d’Autume, Mihaela Rosca, Jack Rae, Shakir Mohamed.
- MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and Accompaniment,Hao-Wen Dong, Wen-Yi Hsiao, Li-Chia Yang, Yi-Hsuan Yang.
- Long Text Generation via Adversarial Training with Leaked Information, Jiaxian Guo, Sidi Lu, Han Cai, Weinan Zhang, Jun Wang, Yong Yu.
- Show, Reward and Tell: Automatic Generation of Narrative Paragraph from Photo Stream by Adversarial Training, Jing Wang, Jianlong Fu, Jinhui Tang, Zechao Li, Tao Mei.
- SentiGAN: Generating Sentimental Texts via Mixture Adversarial Networks, Ke Wang, Xiaojun Wan.
- Adversarial Active Learning for Sequences Labeling and Generation, Yue Deng, KaWai Chen, Yilin Shen, Hongxia Jin.
- One “Ruler” for All Languages: Multi-Lingual Dialogue Evaluation with Adversarial Multi-Task Learning, Xiaowei Tong, Zhenxin Fu, Mingyue Shang, Dongyan Zhao, Rui Yan.
- No Metrics Are Perfect: Adversarial Reward Learning for Visual Storytelling, Xin Wang, Wenhu Chen, Yuan-Fang Wang, William Yang Wang.
- Generating Natural Language Adversarial Examples, Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, Bo-Jhang Ho, Mani Srivastava, Kai-Wei Chang.
- Generating Classical Chinese Poems via Conditional Variational Autoencoder and Adversarial Training, Juntao Li, Yan Song, Haisong Zhang, Dongmin Chen, Shuming Shi, Dongyan Zhao, Rui Yan.
- Diversity-Promoting GAN: A Cross-Entropy Based Generative Adversarial Network for Diversified Text Generation, Jingjing Xu, Xuancheng Ren, Junyang Lin, Xu Sun.
- Learning to Encode Text as Human-Readable Summaries using Generative Adversarial Networks, Yaushian Wang, Hung-Yi Lee.
- Improving Neural Machine Translation with Conditional Sequence Generative Adversarial Nets, Zhen Yang, Wei Chen, Feng Wang and Bo Xu.
- Adversarial Example Generation with Syntactically Controlled Paraphrase Networks, Mohit Iyyer, John Wieting, Kevin Gimpel and Luke Zettlemoyer.
- MGAN: Training Generative Adversarial Nets with Multiple Generators, Quan Hoang, Tu Dinh Nguyen, Trung Le, Dinh Phung.
- MaskGAN: Better Text Generation via Filling in the ______, William Fedus, Ian Goodfellow, Andrew M. Dai.
- Unsupervised Cipher Cracking Using Discrete GANs, Aidan N. Gomez, Sicong Huang, Ivan Zhang, Bryan M. Li, Muhammad Osama, Lukasz Kaiser.
- RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks, Jinsung Yoon, James Jordon, Mihaela Schaar.
- Towards Text Generation with Adversarially Learned Neural Outlines, Sandeep Subramanian, Sai Rajeswar Mudumba, Alessandro Sordoni, Adam Trischler, Aaron Courville, Chris Pal.
- Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization, Yizhe Zhang, Michel Galley, Jianfeng Gao, Zhe Gan, Xiujun Li, Chris Brockett, Bill Dolan.
- Adversarial Text Generation via Feature-Mover's Distance, Liqun Chen, Shuyang Dai, Chenyang Tao, Dinghan Shen, Zhe Gan, Haichao Zhang, Yizhe Zhang, Lawrence Carin.
- SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient, Lantao Yu, Weinan Zhang, Jun Wang and Yong Yu.
- Contextual RNN-GANs for Abstract Reasoning Diagram Generation, Viveka Kulharia, Arnab Ghosh, Amitabha Mukerjee, Vinay Namboodiri and Mohit Bansal.
- Multimodal Storytelling via Generative Adversarial Imitation Learning, Zhiqian Chen, Xuchao Zhang, Arnold Boedihardjo, Jing Dai, Chang-Tien Lu.
- Neural Response Generation via GAN with an Approximate Embedding Layer, Zhen Xu, Bingquan Liu, Baoxun Wang, Chengjie Sun, Xiaolong Wang, Zhuoran Wang, Chao Qi.
- Adversarial Learning for Neural Dialogue Generation, Jiwei Li, Will Monroe, Tianlin Shi, Sébastien Jean, Alan Ritter, Dan Jurafsky.
- Adversarial Feature Matching for Text Generation, Yizhe Zhang (Duke university) · zhe gan () · Kai Fan () · Zhi Chen (Duke University) · Ricardo Henao (Duke University) · Lawrence Carin (Duke).
- Learning Texture Manifolds with the Periodic Spatial GAN, Nikolay Jetchev (Zalando Research) · Urs M Bergmann (Zalando Research) · Roland Vollgraf (Zalando Research).
- Adversarial Ranking for Language Generation, Kevin Lin, Dianqi Li, Xiaodong He, Zhengyou Zhang, Ming-ting Sun.
- Maximum-Likelihood Augmented Discrete Generative Adversarial Networks, Tong Che, Yanran Li, Ruixiang Zhang, R Devon Hjelm, Wenjie Li, Yangqiu Song, Yoshua Bengio.