Fetching the paper…
Reading the bibliography…
Paraphrase generation is a longstanding important problem in natural language processing.
Differentiable subset sampling
Sang Michael Xie and Stefano Ermon · 1901
Earlier work this paper cites.
Wouter Kool, Herke van Hoof, and Max Welling · 1903
Earlier work this paper cites.
Paraphrasing questions using given and new information
Kathleen R McKeown · 1983
Earlier work this paper cites.
Wordnet: a lexical database for english
George A Miller · 1995
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
Earlier work this paper cites.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
Earlier work this paper cites.
Synonymous paraphrasing using wordnet and internet
Igor A Bolshakov and Alexander Gelbukh · 2004
Earlier work this paper cites.
Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
Earlier work this paper cites.
Paraphrasing for automatic evaluation
David Kauchak and Regina Barzilay · 2006
Earlier work this paper cites.
Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
Earlier work this paper cites.
Learning phrase representations using rnn encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge J. Belongie, Lubomir D. Bourdev, Ross B. Girshick, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C. Lawrence Zitnick · 2014
Earlier work this paper cites.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V. Le · 2014
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2015
Earlier work this paper cites.
Ppdb 2.0: Better paraphrase ranking, fine-grained entailment relations, word embeddings, and style classification
Ellie Pavlick, Pushpendre Rastogi, Juri Ganitkevich, Benjamin Van Durme, and Chris Callison-Burch · 2015
Earlier work this paper cites.
Generating sentences from a continuous space
Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, Andrew M. Dai, Rafal Józefowicz, and Samy Bengio · 2016
Earlier work this paper cites.
Incorporating copying mechanism in sequence-to-sequence learning
Jiatao Gu, Zhengdong Lu, Hang Li, and Victor O.K. Li · 2016
Earlier work this paper cites.
Chia-Wei Liu, Ryan Lowe, Iulian V Serban, Michael Noseworthy, Laurent Charlin, and Joelle Pineau · 2016
Cited alongside, same era.
Paraphrase generation from latent-variable pcfgs for semantic parsing
Shashi Narayan, Siva Reddy, and Shay B Cohen · 2016
Cited alongside, same era.
Neural paraphrase generation with stacked residual lstm networks
Aaditya Prakash, Sadid A. Hasan, Kathy Lee, Vivek Datla, Ashequl Qadir, Joey Liu, and Oladimeji Farri · 2016
Cited alongside, same era.
Generalization and equilibrium in generative adversarial nets (gans)
Sanjeev Arora, Rong Ge, Yingyu Liang, Tengyu Ma, and Yi Zhang · 2017
Cited alongside, same era.
Joint copying and restricted generation for paraphrase
Ziqiang Cao, Chuwei Luo, Wenjie Li, and Sujian Li · 2017
Cited alongside, same era.
Deep generative models for natual language processing
Yao Fu · 2018
Later among the works it cites.
End-to-end content and plan selection for data-to-text generation
Sebastian Gehrmann, Falcon Z. Dai, Henry Elder, and Alexander M. Rush · 2018
Later among the works it cites.
A deep generative framework for paraphrase generation
Ankush Gupta, Arvind Agarwal, Prawaan Singh, and Piyush Rai · 2018
Later among the works it cites.
A tutorial on deep latent variable models of natural language
Yoon Kim, Sam Wiseman, and Alexander M. Rush · 2018
Later among the works it cites.
Paraphrase generation with deep reinforcement learning
Zichao Li, Xin Jiang, Lifeng Shang, and Hang Li · 2018
Later among the works it cites.
Table-to-text generation by structure-aware seq2seq learning
Tianyu Liu, Kexiang Wang, Lei Sha, Baobao Chang, and Zhifang Sui · 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Learning to paraphrase for question answering
Li Dong, Jonathan Mallinson, Siva Reddy, and Mirella Lapata · 2017
Cited alongside, same era.
beta-vae: Learning basic visual concepts with a constrained variational framework
Irina Higgins, Loïc Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner · 2017
Cited alongside, same era.
Lexically constrained decoding for sequence generation using grid beam search
Chris Hokamp and Qun Liu · 2017
Cited alongside, same era.
Categorical reparameterization with gumbel-softmax
Eric Jang, Shixiang Gu, and Ben Poole · 2017
Cited alongside, same era.
The concrete distribution: A continuous relaxation of discrete random variables
Chris J. Maddison, Andriy Mnih, and Yee Whye Teh · 2017
Cited alongside, same era.
Why we need new evaluation metrics for nlg
Jekaterina Novikova, Ondrej Dusek, Amanda Cercas Curry, and Verena Rieser · 2017
Cited alongside, same era.
Cross-domain semantic parsing via paraphrasing
Yu Su and Xifeng Yan · 2017
Cited alongside, same era.
Later among the works it cites.
Bag-of-words as target for neural machine translation
Shuming Ma, Xu Sun, Yizhong Wang, and Junyang Lin · 2018
Later among the works it cites.
Order-planning neural text generation from structured data
Lei Sha, Lili Mou, Tianyu Liu, Pascal Poupart, Sujian Li, Baobao Chang, and Zhifang Sui · 2018
Later among the works it cites.
No metrics are perfect: Adversarial reward learning for visual storytelling
Xin Wang, Wenhu Chen, Yuan-Fang Wang, and William Yang Wang · 2018
Later among the works it cites.
Learning neural templates for text generation
Sam Wiseman, Stuart M. Shieber, and Alexander M. Rush · 2018
Later among the works it cites.
Spherical latent spaces for stable variational autoencoders
Jiacheng Xu and Greg Durrett · 2018
Later among the works it cites.
Adversarially regularized autoencoders
Junbo Jake Zhao, Yoon Kim, Kelly Zhang, Alexander M. Rush, and Yann LeCun · 2018
Later among the works it cites.
Lagging inference networks and posterior collapse in variational autoencoders
Junxian He, Daniel Spokoyny, Graham Neubig, and Taylor Berg-Kirkpatrick · 2019
Later among the works it cites.
Step-by-step: Separating planning from realization in neural data-to-text generation
Amit Moryossef, Yoav Goldberg, and Ido Dagan · 2019
Later among the works it cites.
Data-to-text generation with content selection and planning
Ratish Puduppully, Li Dong, and Mirella Lapata · 2019
Later among the works it cites.
Topic-guided variational autoencoders for text generation
Wenlin Wang, Zhe Gan, Hongteng Xu, Ruiyi Zhang, Guoyin Wang, Dinghan Shen, Changyou Chen, and Lawrence Carin · 2019
Later among the works it cites.
Latent normalizing flows for discrete sequences
Zachary M. Ziegler and Alexander M. Rush · 2019
Later among the works it cites.