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Paraphrase generation is a fundamental and long-standing task in natural language processing.
Megatron-lm: Training multi-billion parameter language models using model parallelism
Shoeybi, M.; Patwary, M.; Puri, R.; LeGresley, P.; Casper, J.; and Catanzaro, B. 2019 · 1909
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Paraphrasing questions using given and new information
McKeown, K. 1983 · 1983
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Bleu: a method for automatic evaluation of machine translation
Papineni, K.; Roukos, S.; Ward, T.; and Zhu, W.-J. 2002 · 2002
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Generation of Single-sentence Paraphrases from Predicate/Argument Structure using Lexico-grammatical Resources
Kozlowski, R.; McCoy, K. F.; and Vijay-Shanker, K. 2003 · 2003
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Unsupervised Construction of Large Paraphrase Corpora: Exploiting Massively Parallel News Sources
Dolan, B.; Quirk, C.; and Brockett, C. 2004 · 2004
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Monolingual Machine Translation for Paraphrase Generation
Quirk, C.; Brockett, C.; and Dolan, W. 2004 · 2004
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Global Autonomous Language Exploitation (GALE)
Olive, J. 2005 · 2005
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A Study of Translation Edit Rate with Targeted Human Annotation
Snover, M.; Dorr, B.; Schwartz, R.; Micciulla, L.; and Makhoul, J. 2006 · 2006
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UNT: SubFinder: Combining Knowledge Sources for Automatic Lexical Substitution
Hassan, S.; Csomai, A.; Banea, C.; Sinha, R.; and Mihalcea, R. 2007 · 2007
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Combining Multiple Resources to Improve SMT-based Paraphrasing Model
Zhao, S.; Niu, C.; Zhou, M.; Liu, T.; and Li, S. 2008 · 2008
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Joint Learning of a Dual SMT System for Paraphrase Generation
Sun, H.; and Zhou, M. 2012 · 2012
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Gaussian Error Linear Units (GELUs)
Hendrycks, D.; and Gimpel, K. 2016 · 2016
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Neural Paraphrase Generation with Stacked Residual LSTM Networks
Prakash, A.; Hasan, S. A.; Lee, K.; Datla, V.; Qadir, A.; Liu, J.; and Farri, O. 2016 · 2016
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Optimizing statistical machine translation for text simplification
Xu, W.; Napoles, C.; Pavlick, E.; Chen, Q.; and Callison-Burch, C. 2016 · 2016
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Joint Copying and Restricted Generation for Paraphrase
Cao, Z.; Luo, C.; Li, W.; and Li, S. 2017 · 2017
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Paraphrasing Revisited with Neural Machine Translation
Mallinson, J.; Sennrich, R.; and Lapata, M. 2017 · 2017
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A Deep Generative Framework for Paraphrase Generation
Gupta, A.; Agarwal, A.; Singh, P.; and Rai, P. 2018 · 2018
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A Retrieve-and-Edit Framework for Predicting Structured Outputs
Hashimoto, T. B.; Guu, K.; Oren, Y.; and Liang, P. 2018 · 2018
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Adversarial Example Generation with Syntactically Controlled Paraphrase Networks
Iyyer, M.; Wieting, J.; Gimpel, K.; and Zettlemoyer, L. 2018 · 2018
Cited alongside, same era.
Paraphrase Generation with Deep Reinforcement Learning
Li, Z.; Jiang, X.; Shang, L.; and Li, H. 2018 · 2018
Cited alongside, same era.
Integrating Transformer and Paraphrase Rules for Sentence Simplification
Zhao, S.; Meng, R.; He, D.; Saptono, A.; and Parmanto, B. 2018 · 2018
Cited alongside, same era.
Controllable Paraphrase Generation with a Syntactic Exemplar
Chen, M.; Tang, Q.; Wiseman, S.; and Gimpel, K. 2019 · 2019
Cited alongside, same era.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2019 · 2019
Cited alongside, same era.
An Empirical Comparison on Imitation Learning and Reinforcement Learning for Paraphrase Generation
DivGAN: Towards Diverse Paraphrase Generation via Diversified Generative Adversarial Network
Cao, Y.; and Wan, X. 2020 · 2020
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Neural Syntactic Preordering for Controlled Paraphrase Generation
Goyal, T.; and Durrett, G. 2020 · 2020
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How can we know what language models know?
Jiang, Z.; Xu, F. F.; Araki, J.; and Neubig, G. 2020 · 2020
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Paraphrase Generation by Learning How to Edit from Samples
Kazemnejad, A.; Salehi, M.; and Soleymani Baghshah, M. 2020 · 2020
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Syntax-Guided Controlled Generation of Paraphrases
Kumar, A.; Ahuja, K.; Vadapalli, R.; and Talukdar, P. 2020 · 2020
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Unsupervised Paraphrasing by Simulated Annealing
Liu, X.; Mou, L.; Meng, F.; Zhou, H.; Zhou, J.; and Song, S. 2020 · 2020
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Du, W.; and Ji, Y. 2019 · 2019
Cited alongside, same era.
Transformer and seq2seq model for Paraphrase Generation
Egonmwan, E.; and Chali, Y. 2019 · 2019
Cited alongside, same era.
Paraphrase Generation with Latent Bag of Words
Fu, Y.; Feng, Y.; and Cunningham, J. P. 2019 · 2019
Cited alongside, same era.
Parameter-Efficient Transfer Learning for NLP
Houlsby, N.; Giurgiu, A.; Jastrzebski, S.; Morrone, B.; De Laroussilhe, Q.; Gesmundo, A.; Attariyan, M.; and Gelly, S. 2019 · 2019
Cited alongside, same era.
Submodular Optimization-based Diverse Paraphrasing and its Effectiveness in Data Augmentation
Kumar, A.; Bhattamishra, S.; Bhandari, M.; and Talukdar, P. 2019 · 2019
Cited alongside, same era.
Decomposable Neural Paraphrase Generation
Li, Z.; Jiang, X.; Shang, L.; and Liu, Q. 2019 · 2019
Cited alongside, same era.
Decoupled Weight Decay Regularization
Loshchilov, I.; and Hutter, F. 2019 · 2019
Cited alongside, same era.
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AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts
Shin, T.; Razeghi, Y.; Logan IV, R. L.; Wallace, E.; and Singh, S. 2020 · 2020
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Transformers: State-of-the-Art Natural Language Processing
Wolf, T.; Debut, L.; Sanh, V.; Chaumond, J.; Delangue, C.; Moi, A.; Cistac, P.; Rault, T.; Louf, R.; Funtowicz, M.; Davison, J.; Shleifer, S.; von Platen, P.; Ma, C.; Jernite, Y.; Plu, J.; Xu, C.; Scao, T. L.; Gugger, S.; Drame, M.; Lhoest, Q.; and Rush, A. M. 2020 · 2020
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ParaSCI: A Large Scientific Paraphrase Dataset for Longer Paraphrase Generation
Dong, Q.; Wan, X.; and Cao, Y. 2021 · 2021
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Making Pre-trained Language Models Better Few-shot Learners
Gao, T.; Fisch, A.; and Chen, D. 2021 · 2021
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Factorising Meaning and Form for Intent-Preserving Paraphrasing
Hosking, T.; and Lapata, M. 2021 · 2021
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LoRA: Low-Rank Adaptation of Large Language Models
Hu, E. J.; Shen, Y.; Wallis, P.; Allen-Zhu, Z.; Li, Y.; Wang, S.; and Chen, W. 2021 · 2021
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Generating Syntactically Controlled Paraphrases without Using Annotated Parallel Pairs
Huang, K.-H.; and Chang, K.-W. 2021 · 2021
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The Power of Scale for Parameter-Efficient Prompt Tuning
Lester, B.; Al-Rfou, R.; and Constant, N. 2021 · 2021
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Prefix-Tuning: Optimizing Continuous Prompts for Generation
Li, X. L.; and Liang, P. 2021 · 2021
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Pushing Paraphrase Away from Original Sentence: A Multi-Round Paraphrase Generation Approach
Lin, Z.; and Wan, X. 2021 · 2021
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Reflective Decoding: Beyond Unidirectional Generation with Off-the-Shelf Language Models
West, P.; Lu, X.; Holtzman, A.; Bhagavatula, C.; Hwang, J. D.; and Choi, Y. 2021 · 2021
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