\begin{thebibliography}{39}
\providecommand{\natexlab}[1]{#1}
\providecommand{\url}[1]{\texttt{#1}}
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  \providecommand{\doi}[1]{doi: #1}\else
  \providecommand{\doi}{doi: \begingroup \urlstyle{rm}\Url}\fi

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Samuel~R Bowman, Luke Vilnis, Oriol Vinyals, Andrew~M Dai, Rafal Jozefowicz,
  and Samy Bengio.
\newblock Generating sentences from a continuous space.
\newblock \emph{arXiv preprint arXiv:1511.06349}, 2015.

\bibitem[Calixto et~al.(2019)Calixto, Rios, and Aziz]{calixto2019latent}
Iacer Calixto, Miguel Rios, and Wilker Aziz.
\newblock Latent variable model for multi-modal translation.
\newblock In \emph{Proc. of ACL}, 2019.

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Fredrik Carlsson, Amaru~Cuba Gyllensten, Evangelia Gogoulou,
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\newblock Semantic re-tuning with contrastive tension.
\newblock In \emph{Proc. of ICLR}, 2021.

\bibitem[Casale et~al.(2018)Casale, Dalca, Saglietti, Listgarten, and
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Francesco~Paolo Casale, Adrian~V. Dalca, Luca Saglietti, Jennifer Listgarten,
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\newblock Gaussian process prior variational autoencoders.
\newblock In \emph{NeurIPS}, 2018.

\bibitem[Chen et~al.(2021)Chen, Liu, Luan, Zhang, Liu, and Sun]{9265406}
Gang Chen, Yang Liu, Huanbo Luan, Meng Zhang, Qun Liu, and Maosong Sun.
\newblock Learning to generate explainable plots for neural story generation.
\newblock \emph{IEEE/ACM Transactions on Audio, Speech, and Language
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\bibitem[Chen et~al.(2020)Chen, Kornblith, Norouzi, and Hinton]{Chen2020ASF}
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey~E. Hinton.
\newblock A simple framework for contrastive learning of visual
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\newblock In \emph{Proc. of ICML}, 2020.

\bibitem[Dai et~al.(2018)Dai, Dai, He, Liu, Liu, Chen, Xiao, and
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Bo~Dai, Hanjun Dai, Niao He, Weiyang Liu, Zhen Liu, Jianshu Chen, Lin Xiao, and
  Le~Song.
\newblock Coupled variational bayes via optimization embedding.
\newblock In S.~Bengio, H.~Wallach, H.~Larochelle, K.~Grauman, N.~Cesa-Bianchi,
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\bibitem[Dai et~al.(2021)Dai, Wang, Park, and Lee]{Dai2021DialogueRG}
Shuyang Dai, Guoyin Wang, Sunghyun Park, and Sungjin Lee.
\newblock Dialogue response generation via contrastive latent representation
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\newblock \emph{Proc. of the 3rd Workshop on Natural Language Processing for
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\bibitem[Deng et~al.(2020)Deng, Bakhtin, Ott, Szlam, and
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Yuntian Deng, Anton Bakhtin, Myle Ott, Arthur Szlam, and Marc'Aurelio Ranzato.
\newblock Residual energy-based models for text generation.
\newblock In \emph{Proc. ICLR}, 2020.

\bibitem[Ding and Gimpel(2021)]{ding-gimpel-2021-flowprior}
Xiaoan Ding and Kevin Gimpel.
\newblock {F}low{P}rior: Learning expressive priors for latent variable
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\newblock In \emph{Proc. of NAACL-HLT}, pages 3242--3258, 2021.

\bibitem[Fang et~al.(2019)Fang, Li, Gao, Dong, and Chen]{Fang_iLVM_2019_EMNLP}
Le~Fang, Chunyuan Li, Jianfeng Gao, Wen Dong, and Changyou Chen.
\newblock Implicit deep latent variable models for text generation.
\newblock In \emph{Proceedings of the 2019 Conference on Empirical Methods in
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\bibitem[Fu et~al.(2019)Fu, Li, Liu, Gao, Celikyilmaz, and
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Hao Fu, Chunyuan Li, Xiaodong Liu, Jianfeng Gao, Asli Celikyilmaz, and Lawrence
  Carin.
\newblock Cyclical annealing schedule: A simple approach to mitigating kl
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\newblock In \emph{NAACL}, 2019.

\bibitem[Gao et~al.(2021)Gao, Yao, and Chen]{Gao2021SimCSESC}
Tianyu Gao, Xingcheng Yao, and Danqi Chen.
\newblock Simcse: Simple contrastive learning of sentence embeddings.
\newblock In \emph{EMNLP}, 2021.

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John Giorgi, Osvald Nitski, Gary~D Bader, and Bo~Wang.
\newblock Declutr: Deep contrastive learning for unsupervised textual
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\newblock In \emph{Proc. of ACL}, 2021.

\bibitem[He et~al.(2019)He, Spokoyny, Neubig, and
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Junxian He, Daniel Spokoyny, Graham Neubig, and Taylor Berg-Kirkpatrick.
\newblock Lagging inference networks and posterior collapse in variational
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\newblock In \emph{Proc. of ICLR}, 2019.

\bibitem[He et~al.(2020)He, Fan, Wu, Xie, and Girshick]{He2020MomentumCF}
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross~B. Girshick.
\newblock Momentum contrast for unsupervised visual representation learning.
\newblock In \emph{Proc. of CVPR}, 2020.

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Kenneth Heafield, Ivan Pouzyrevsky, Jonathan~H. Clark, and Philipp Koehn.
\newblock Scalable modified {Kneser-Ney} language model estimation.
\newblock In \emph{Proc. of ACL}, 2013.

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Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot,
  Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner.
\newblock beta-vae: Learning basic visual concepts with a constrained
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\newblock In \emph{Proc. of ICLR}, 2017.

\bibitem[Hjelm et~al.(2019)Hjelm, Fedorov, Lavoie-Marchildon, Grewal,
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R.~Devon Hjelm, A.~Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Adam
  Trischler, and Yoshua Bengio.
\newblock Learning deep representations by mutual information estimation and
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\newblock In \emph{Proc. of ICLR}, 2019.

\bibitem[Hochreiter and Schmidhuber(1997)]{hochreiter1997long}
Sepp Hochreiter and J{\"u}rgen Schmidhuber.
\newblock Long short-term memory.
\newblock \emph{Neural computation}, 9\penalty0 (8):\penalty0 1735--1780, 1997.

\bibitem[Jhamtani and
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Harsh Jhamtani and Taylor Berg-Kirkpatrick.
\newblock Narrative text generation with a latent discrete plan.
\newblock In \emph{Findings of EMNLP 2020}, 2020.

\bibitem[Khosla et~al.(2020)Khosla, Teterwak, Wang, Sarna, Tian, Isola,
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Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip
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\newblock Supervised contrastive learning.
\newblock In \emph{Proc. of NeurIPS}, volume~33, pages 18661--18673, 2020.

\bibitem[Kim et~al.(2017)Kim, Zhang, Rush, LeCun, et~al.]{kim2017adversarially}
Yoon Kim, Kelly Zhang, Alexander~M Rush, Yann LeCun, et~al.
\newblock Adversarially regularized autoencoders.
\newblock \emph{arXiv preprint arXiv:1706.04223}, 2017.

\bibitem[Kim et~al.(2018)Kim, Wiseman, Miller, Sontag, and Rush]{kim2018semi}
Yoon Kim, Sam Wiseman, Andrew Miller, David Sontag, and Alexander Rush.
\newblock Semi-amortized variational autoencoders.
\newblock In \emph{Proc. of ICML}, pages 2683--2692, 2018.

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Phuc~H Le-Khac, Graham Healy, and Alan~F Smeaton.
\newblock Contrastive representation learning: A framework and review.
\newblock \emph{IEEE Access}, 8:\penalty0 193907--193934, 2020.

\bibitem[Lee et~al.(2021)Lee, Lee, and Hwang]{lee2021contrastive}
Seanie Lee, Dong~Bok Lee, and Sung~Ju Hwang.
\newblock Contrastive learning with adversarial perturbations for conditional
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\newblock In \emph{International Conference on Learning Representations}, 2021.

\bibitem[Liang et~al.(2021)Liang, Wu, Li, Wang, Meng, Qin, Chen, Zhang, and
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Xiaobo Liang, Lijun Wu, Juntao Li, Yue Wang, Qi~Meng, Tao Qin, Wei Chen, Min
  Zhang, and Tie-Yan Liu.
\newblock R-drop: Regularized dropout for neural networks.
\newblock In \emph{NeurIPS}, 2021.

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Mitchell Marcus, Beatrice Santorini, and Mary~Ann Marcinkiewicz.
\newblock Building a large annotated corpus of english: The penn treebank.
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\bibitem[Oord et~al.(2018)Oord, Li, and Vinyals]{Oord2018RepresentationLW}
A.~Oord, Y.~Li, and Oriol Vinyals.
\newblock Representation learning with contrastive predictive coding.
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\bibitem[Pang et~al.(2020)Pang, Han, Nijkamp, Zhu, and Wu]{NEURIPS2020_pang}
Bo~Pang, Tian Han, Erik Nijkamp, Song-Chun Zhu, and Ying~Nian Wu.
\newblock Learning latent space energy-based prior model.
\newblock In \emph{Proc. of NeurIPS}, 2020.

\bibitem[Rockafellar et~al.(1966)]{rockafellar1966extension}
R~Tyrrell Rockafellar et~al.
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\bibitem[Shen et~al.(2017)Shen, Su, Li, Li, Niu, Zhao, Aizawa, and
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Xiaoyu Shen, Hui Su, Yanran Li, Wenjie Li, Shuzi Niu, Yang Zhao, Akiko Aizawa,
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\newblock A conditional variational framework for dialog generation.
\newblock In \emph{Proc. of ACL}, pages 504--509, 2017.

\bibitem[Su et~al.(2022)Su, Lan, Wang, Yogatama, Kong, and Collier]{Su2022ACF}
Yixuan Su, Tian Lan, Yan Wang, Dani Yogatama, Lingpeng Kong, and Nigel Collier.
\newblock A contrastive framework for neural text generation.
\newblock \emph{ArXiv}, abs/2202.06417, 2022.

\bibitem[Sun et~al.(2020)Sun, Cheng, Zhang, Zhang, Zheng, Wang, and
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Yifan Sun, Changmao Cheng, Yuhan Zhang, Chi Zhang, Liang Zheng, Zhongdao Wang,
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\newblock Circle loss: A unified perspective of pair similarity optimization.
\newblock \emph{Proc. of CVPR}, 2020.

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Ilya Sutskever, Oriol Vinyals, and Quoc~V. Le.
\newblock Sequence to sequence learning with neural networks.
\newblock In \emph{NeurIPS}, 2014.

\bibitem[Tomczak and Welling(2018)]{Tomczak2018VAEWA}
Jakub~M. Tomczak and Max Welling.
\newblock Vae with a vampprior.
\newblock In \emph{AISTATS}, 2018.

\bibitem[Wang and Wang(2019)]{wang-wang-2019-riemannian}
Prince~Zizhuang Wang and William~Yang Wang.
\newblock {R}iemannian normalizing flow on variational {W}asserstein
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\newblock In \emph{Proc. of NAACL-HLT}, pages 284--294, 2019.

\bibitem[Yang et~al.(2017)Yang, Hu, Salakhutdinov, and
  Berg-Kirkpatrick]{yang2017improved}
Zichao Yang, Zhiting Hu, Ruslan Salakhutdinov, and Taylor Berg-Kirkpatrick.
\newblock Improved variational autoencoders for text modeling using dilated
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\newblock In \emph{Proc. of ICML}, 2017.

\bibitem[Zhang et~al.(2020)Zhang, He, Liu, Lim, and
  Bing]{zhang2020unsupervised}
Yan Zhang, Ruidan He, Zuozhu Liu, Kwan~Hui Lim, and Lidong Bing.
\newblock An unsupervised sentence embedding method by mutual information
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\newblock In \emph{Proc. of EMNLP}, 2020.

\end{thebibliography}
