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Diffusion models have achieved state-of-the-art synthesis quality on both visual and audio tasks, and recent works further adapt them to textual data by diffusing on the embedding space.
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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English gigaword
David Graff, Junbo Kong, Ke Chen, and Kazuaki Maeda. 2003 · 2003
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Minimum bayes-risk decoding for statistical machine translation
Shankar Kumar and William Byrne. 2004 · 2004
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Findings of the 2014 workshop on statistical machine translation
Ondřej Bojar, Christian Buck, Christian Federmann, Barry Haddow, Philipp Koehn, Johannes Leveling, Christof Monz, Pavel Pecina, Matt Post, Herve Saint-Amand, et al. 2014 · 2014
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Report on the 11th iwslt evaluation campaign
Mauro Cettolo, Jan Niehues, Sebastian Stüker, Luisa Bentivogli, and Marcello Federico. 2014 · 2014
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Generative adversarial nets
J Goodfellow Ian, Pouget-Abadie Jean, Mirza Mehdi, Xu Bing, Warde-Farley David, Ozair Sherjil, and C Courville Aaron. 2014 · 2014
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A neural attention model for abstractive sentence summarization
Alexander M Rush, Sumit Chopra, and Jason Weston. 2015 · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli. 2015 · 2015
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Findings of the 2016 conference on machine translation (wmt16)
Ondrej Bojar, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Varvara Logacheva, Christof Monz, et al. 2016 · 2016
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Sequence-level knowledge distillation
Yoon Kim and Alexander M Rush. 2016 · 2016
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Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
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Quasar: Datasets for question answering by search and reading
Bhuwan Dhingra, Kathryn Mazaitis, and William W. Cohen. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Representation degeneration problem in training natural language generation models
Jun Gao, Di He, Xu Tan, Tao Qin, Liwei Wang, and Tieyan Liu. 2018 · 2018
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Non-autoregressive neural machine translation
Jiatao Gu, James Bradbury, Caiming Xiong, Victor OK Li, and Richard Socher. 2018 · 2018
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Deterministic non-autoregressive neural sequence modeling by iterative refinement
Jason Lee, Elman Mansimov, and Kyunghyun Cho. 2018 · 2018
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A call for clarity in reporting bleu scores
Matt Post. 2018 · 2018
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Fast, diverse and accurate image captioning guided by part-of-speech
Aditya Deshpande, Jyoti Aneja, Liwei Wang, Alexander G Schwing, and David Forsyth. 2019 · 2019
Cited alongside, same era.
How contextual are contextualized word representations? comparing the geometry of bert, elmo, and gpt-2 embeddings
Kawin Ethayarajh. 2019 · 2019
Cited alongside, same era.
Mask-predict: Parallel decoding of conditional masked language models
Marjan Ghazvininejad, Omer Levy, Yinhan Liu, and Luke Zettlemoyer. 2019 · 2019
Cited alongside, same era.
Levenshtein transformer
Jiatao Gu, Changhan Wang, and Junbo Zhao. 2019 · 2019
Cited alongside, same era.
Non-autoregressive neural machine translation with enhanced decoder input
Junliang Guo, Xu Tan, Di He, Tao Qin, Linli Xu, and Tie-Yan Liu. 2019 · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans. 2021 · 2021
Later among the works it cites.
Argmax flows and multinomial diffusion: Learning categorical distributions
Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, and Max Welling. 2021 · 2021
Later among the works it cites.
Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal. 2021 · 2021
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Step-unrolled denoising autoencoders for text generation
Nikolay Savinov, Junyoung Chung, Mikolaj Binkowski, Erich Elsen, and Aaron van den Oord. 2021 · 2021
Later among the works it cites.
Analog bits: Generating discrete data using diffusion models with self-conditioning
Ting Chen, Ruixiang ZHANG, and Geoffrey Hinton. 2022 · 2022
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Cited alongside, same era.
Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi. 2019 · 2019
Cited alongside, same era.
Wavegrad: Estimating gradients for waveform generation
Nanxin Chen, Yu Zhang, Heiga Zen, Ron J Weiss, Mohammad Norouzi, and William Chan. 2020 · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020 · 2020
Cited alongside, same era.
Neural crf model for sentence alignment in text simplification
Chao Jiang, Mounica Maddela, Wuwei Lan, Yang Zhong, and Wei Xu. 2020 · 2020
Cited alongside, same era.
Non-autoregressive machine translation with disentangled context transformer
Jungo Kasai, James Cross, Marjan Ghazvininejad, and Jiatao Gu. 2020 · 2020
Cited alongside, same era.
Diffwave: A versatile diffusion model for audio synthesis
Zhifeng Kong, Wei Ping, Jiaji Huang, Kexin Zhao, and Bryan Catanzaro. 2020 · 2020
Cited alongside, same era.
Sander Dieleman, Laurent Sartran, Arman Roshannai, Nikolay Savinov, Yaroslav Ganin, Pierre H. Richemond, Arnaud Doucet, Robin Strudel, Chris Dyer, Conor Durkan, Curtis Hawthorne, Rémi Leblond, Will Grathwohl, and Jonas Adler. 2022 · 2022
Closest in time.
Diverse text generation via variational encoder-decoder models with gaussian process priors
Wanyu Du, Jianqiao Zhao, Liwei Wang, and Yangfeng Ji. 2022 · 2022
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Diffuseq: Sequence to sequence text generation with diffusion models
Shansan Gong, Mukai Li, Jiangtao Feng, Zhiyong Wu, and Lingpeng Kong. 2022 · 2022
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Directed acyclic transformer for non-autoregressive machine translation
Fei Huang, Hao Zhou, Yang Liu, Hang Li, and Minlie Huang. 2022 · 2022
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Diffusion-lm improves controllable text generation
Xiang Li, John Thickstun, Ishaan Gulrajani, Percy S Liang, and Tatsunori B Hashimoto. 2022 · 2022
Closest in time.
Diffuser: Discrete diffusion via edit-based reconstruction
Machel Reid, Vincent J. Hellendoorn, and Graham Neubig. 2022 · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. 2022 · 2022
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Self-conditioned embedding diffusion for text generation
Robin Strudel, Corentin Tallec, Florent Altché, Yilun Du, Yaroslav Ganin, Arthur Mensch, Will Grathwohl, Nikolay Savinov, Sander Dieleman, Laurent Sifre, and Rémi Leblond. 2022 · 2022
Closest in time.
One transformer fits all distributions in multi-modal diffusion at scale
Fan Bao, Shen Nie, Kaiwen Xue, Chongxuan Li, Shi Pu, Yaole Wang, Gang Yue, Yue Cao, Hang Su, and Jun Zhu. 2023 · 2023
Closest in time.
Ssd-lm: Semi-autoregressive simplex-based diffusion language model for text generation and modular control
Xiaochuang Han, Sachin Kumar, and Yulia Tsvetkov. 2023 · 2023
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Dinoiser: Diffused conditional sequence learning by manipulating noises
Jiasheng Ye, Zaixiang Zheng, Yu Bao, Lihua Qian, and Mingxuan Wang. 2023 · 2023
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Seqdiffuseq: Text diffusion with encoder-decoder transformers
Hongyi Yuan, Zheng Yuan, Chuanqi Tan, Fei Huang, and Songfang Huang. 2023 · 2023
Closest in time.
Any-to-any generation via composable diffusion
Zineng Tang, Ziyi Yang, Chenguang Zhu, Michael Zeng, and Mohit Bansal. 2024 · 2024
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