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Variational autoencoders (VAEs) have received much attention recently as an end-to-end architecture for text generation with latent variables.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling. 2013 · 2013
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Neural machine translation by jointly learning to align and translate. in international conference on learning representations
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
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Adversarial autoencoder
Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, and Ian Goodfellow. 2015 · 2015
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
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Generating sentences from a continuous space
Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, Andrew M. Dai, Rafal Józefowicz, and Samy Bengio. 2016 · 2016
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Xi Chen, Diederik P Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, and Pieter Abbeel. 2016 · 2016
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Abstractive sentence summarization with attentive recurrent neural networks
Sumit Chopra, Michael Auli, and Alexander M. Rush. 2016 · 2016
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Pixelvae: A latent variable model for natural images
Ishaan Gulrajani, Kundan Kumar, Faruk Ahmed, Adrien Ali Taiga, Francesco Visin, David Vazquez, and Aaron Courville. 2016 · 2016
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Neural variational inference for text processing
Yishu Miao, Lei Yu, and Phil Blunsom. 2016 · 2016
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Hierarchical attention networks for document classification
Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, and Eduard Hovy. 2016 · 2016
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Martin Arjovsky, Soumith Chintala, and Léon Bottou. 2017 · 2017
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Z-forcing: Training stochastic recurrent networks
Anirudh Goyal, Alessandro Sordoni, Marc-Alexandre Côté, Nan Rosemary Ke, and Yoshua Bengio. 2017 · 2017
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Toward controlled generation of text
Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, and Eric P. Xing. 2017 · 2017
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Discovering discrete latent topics with neural variational inference
Yishu Miao, Edward Grefenstette, and Phil Blunsom. 2017 · 2017
Earlier work this paper cites.
A hybrid convolutional variational autoencoder for text generation
Stanislau Semeniuta, Aliaksei Severyn, and Erhardt Barth. 2017 · 2017
Cited alongside, same era.
A hierarchical latent variable encoder-decoder model for generating dialogues
Iulian Serban, Alessandro Sordoni, Ryan Lowe, Laurent Charlin, Joelle Pineau, Aaron C. Courville, and Yoshua Bengio. 2017 · 2017
Cited alongside, same era.
Twin networks: Using the future as a regularizer
Dmitriy Serdyuk, Nan Rosemary Ke, Alessandro Sordoni, Christopher Joseph Pal, and Yoshua Bengio. 2017 · 2017
Cited alongside, same era.
A conditional variational framework for dialog generation
Xiaoyu Shen, Hui Su, Yanran Li, Wenjie Li, Shuzi Niu, Yang Zhao, Akiko Aizawa, and Guoping Long. 2017 · 2017
Cited alongside, same era.
Improved variational autoencoders for text modeling using dilated convolutions
Zichao Yang, Zhiting Hu, Ruslan Salakhutdinov, and Taylor Berg-Kirkpatrick. 2017 · 2017
Cited alongside, same era.
A retrieve-and-edit framework for predicting structured outputs
Tatsunori B Hashimoto, Kelvin Guu, Yonatan Oren, and Percy S Liang. 2018 · 2018
Later among the works it cites.
Learning to write with cooperative discriminators
Ari Holtzman, Jan Buys, Maxwell Forbes, Antoine Bosselut, David Golub, and Yejin Choi. 2018 · 2018
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Fast decoding in sequence models using discrete latent variables
Lukasz Kaiser, Aurko Roy, Ashish Vaswani, Niki Parmar, Samy Bengio, Jakob Uszkoreit, and Noam Shazeer. 2018 · 2018
Later among the works it cites.
Semi-amortized variational autoencoders
Yoon Kim, Sam Wiseman, Andrew C. Miller, David A Sontag, and Alexander M. Rush. 2018 · 2018
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A hierarchical latent structure for variational conversation modeling
Yookoon Park, Jaemin Cho, and Gunhee Kim. 2018 · 2018
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A hierarchical latent vector model for learning long-term structure in music
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Seqgan: Sequence generative adversarial nets with policy gradient
Lantao Yu, Weinan Zhang, Jun Wang, and Yong Yu. 2017 · 2017
Cited alongside, same era.
Adversarial feature matching for text generation
Yizhe Zhang, Zhe Gan, Kai Fan, Zhi Chen, Ricardo Henao, Dinghan Shen, and Lawrence Carin. 2017 · 2017
Cited alongside, same era.
Learning discourse-level diversity for neural dialog models using conditional variational autoencoders
Tiancheng Zhao, Ran Zhao, and Maxine Eskénazi. 2017 · 2017
Cited alongside, same era.
Variational attention for sequence-to-sequence models
Hareesh Bahuleyan, Lili Mou, Olga Vechtomova, and Pascal Poupart. 2018 · 2018
Cited alongside, same era.
Eval all, trust a few, do wrong to none: Comparing sentence generation models
Ondřej Cífka, Aliaksei Severyn, Enrique Alfonseca, and Katja Filippova. 2018 · 2018
Cited alongside, same era.
Latent alignment and variational attention
Yuntian Deng, Yoon Kim, Justin Chiu, Demi Guo, and Alexander M. Rush. 2018 · 2018
Cited alongside, same era.
Variational autoregressive decoder for neural response generation
Jiachen Du, Wenjie Li, Yulan He, Ruifeng Xu, Lidong Bing, and Xuan Wang. 2018 · 2018
Cited alongside, same era.
Adam Roberts, Jesse Engel, Colin Raffel, Curtis Hawthorne, and Douglas Eck. 2018 · 2018
Later among the works it cites.
Generative neural machine translation
Harshil Shah and David Barber. 2018 · 2018
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Spherical latent spaces for stable variational autoencoders
Jiacheng Xu and Greg Durrett. 2018 · 2018
Later among the works it cites.
Structvae: Tree-structured latent variable models for semi-supervised semantic parsing
Pengcheng Yin, Chunting Zhou, Junxian He, and Graham Neubig. 2018 · 2018
Later among the works it cites.
Generating informative and diverse conversational responses via adversarial information maximization
Yizhe Zhang, Michel Galley, Jianfeng Gao, Zhe Gan, Xiujun Li, Chris Brockett, and Bill Dolan. 2018 · 2018
Later among the works it cites.
Texygen: A benchmarking platform for text generation models
Yaoming Zhu, Sidi Lu, Lei Zheng, Jiaxian Guo, Weinan Zhang, Jun Wang, and Yong Yu. 2018 · 2018
Later among the works it cites.
Cyclical annealing schedule: A simple approach to mitigate kl vanishing
Hao Fu, Chunyuan Li, Xiaodong Liu, Jianfeng Gao, Asli Celikyilmaz, and Lawrence Carin. 2019 · 2019
Closest in time.
Lagging inference networks and posterior collapse in variational autoencoders
Junxian He, Daniel Spokoyny, Graham Neubig, and Taylor Berg-Kirkpatrick. 2019 · 2019
Closest in time.
Topic-guided variational autoencoders for text generation
Wenlin Wang, Zhe Gan, Hongteng Xu, Ruiyi Zhang, Yingxu Wang, Dinghan Shen, Changyou Chen, and Lawrence Carin. 2019 · 2019
Closest in time.