Fetching the paper…
Reading the bibliography…
Non-autoregressive Transformer (NAT) is a family of text generation models, which aims to reduce the decoding latency by predicting the whole sentences in parallel.
Non-autoregressive transformer by position learning
Bao, Y., Zhou, H., Feng, J., Wang, M., Huang, S., Chen, J., and Li, L · 1911
Earlier work this paper cites.
Information theoretical analysis of multivariate correlation
Watanabe, M. S · 1960
Earlier work this paper cites.
Information theory and an extension of the maximum likelihood principle
Akaike, H · 1998
Earlier work this paper cites.
The multiinformation function as a tool for measuring stochastic dependence
Studený, M. and Vejnarová, J · 1998
Earlier work this paper cites.
Bleu: a method for automatic evaluation of machine translation
Papineni, K., Roukos, S., Ward, T., and Zhu, W · 2002
Earlier work this paper cites.
A tutorial on variational bayesian inference
Fox, C. W. and Roberts, S. J · 2012
Earlier work this paper cites.
Sequence-level knowledge distillation
Kim, Y. and Rush, A. M · 2016
Earlier work this paper cites.
Neural machine translation of rare words with subword units
Sennrich, R., Haddow, B., and Birch, A · 2016
Earlier work this paper cites.
Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., and Polosukhin, I · 2017
Earlier work this paper cites.
Non-autoregressive neural machine translation
Gu, J., Bradbury, J., Xiong, C., Li, V. O. K., and Socher, R · 2018
Earlier work this paper cites.
Achieving human parity on automatic chinese to english news translation
Hassan, H., Aue, A., Chen, C., Chowdhary, V., Clark, J., Federmann, C., Huang, X., Junczys-Dowmunt, M., Lewis, W., Li, M., Liu, S., Liu, T., Luo, R., Menezes, A., Qin, T., Seide, F., Tan, X., Tian, F., Wu, L., Wu, S., Xia, Y., Zhang, D., Zhang, Z., and Zhou, M · 2018
Earlier work this paper cites.
Fast decoding in sequence models using discrete latent variables
Kaiser, L., Bengio, S., Roy, A., Vaswani, A., Parmar, N., Uszkoreit, J., and Shazeer, N · 2018
Earlier work this paper cites.
Deterministic non-autoregressive neural sequence modeling by iterative refinement
Lee, J., Mansimov, E., and Cho, K · 2018
Earlier work this paper cites.
End-to-end non-autoregressive neural machine translation with connectionist temporal classification
Libovický, J. and Helcl, J · 2018
Earlier work this paper cites.
Analyzing uncertainty in neural machine translation
Ott, M., Auli, M., Grangier, D., and Ranzato, M · 2018
Earlier work this paper cites.
Mask-predict: Parallel decoding of conditional masked language models
Ghazvininejad, M., Levy, O., Liu, Y., and Zettlemoyer, L · 2019
Cited alongside, same era.
Levenshtein transformer
Gu, J., Wang, C., and Zhao, J · 2019
Cited alongside, same era.
Flowseq: Non-autoregressive conditional sequence generation with generative flow
Ma, X., Zhou, C., Li, X., Neubig, G., and Hovy, E. H · 2019
Cited alongside, same era.
fairseq: A fast, extensible toolkit for sequence modeling
Ott, M., Edunov, S., Baevski, A., Fan, A., Gross, S., Ng, N., Grangier, D., and Auli, M · 2019
Cited alongside, same era.
Fast structured decoding for sequence models
Sun, Z., Li, Z., Wang, H., He, D., Lin, Z., and Deng, Z · 2019
Cited alongside, same era.
Imitation learning for non-autoregressive neural machine translation
Wei, B., Wang, M., Zhou, H., Lin, J., and Sun, X · 2019
Cited alongside, same era.
Understanding knowledge distillation in non-autoregressive machine translation
Zhou, C., Gu, J., and Neubig, G · 2020
Later among the works it cites.
Non-autoregressive translation by learning target categorical codes
Bao, Y., Huang, S., Xiao, T., Wang, D., Dai, X., and Chen, J · 2021
Later among the works it cites.
Understanding and improving lexical choice in non-autoregressive translation
Ding, L., Wang, L., Liu, X., Wong, D. F., Tao, D., and Tu, Z · 2021
Later among the works it cites.
Rejuvenating low-frequency words: Making the most of parallel data in non-autoregressive translation
Ding, L., Wang, L., Liu, X., Wong, D. F., Tao, D., and Tu, Z · 2021
Later among the works it cites.
Order-agnostic cross entropy for non-autoregressive machine translation
Du, C., Tu, Z., and Jiang, J · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Imitation learning for non-autoregressive neural machine translation
Wei, B., Wang, M., Zhou, H., Lin, J., and Sun, X · 2019
Cited alongside, same era.
Aligned cross entropy for non-autoregressive machine translation
Ghazvininejad, M., Karpukhin, V., Zettlemoyer, L., and Levy, O · 2020
Cited alongside, same era.
Jointly masked sequence-to-sequence model for non-autoregressive neural machine translation
Guo, J., Xu, L., and Chen, E · 2020
Cited alongside, same era.
Non-autoregressive machine translation with disentangled context transformer
Kasai, J., Cross, J., Ghazvininejad, M., and Gu, J · 2020
Cited alongside, same era.
Non-autoregressive machine translation with latent alignments
Saharia, C., Chan, W., Saxena, S., and Norouzi, M · 2020
Cited alongside, same era.
Minimizing the bag-of-ngrams difference for non-autoregressive neural machine translation
Shao, C., Zhang, J., Feng, Y., Meng, F., and Zhou, J · 2020
Cited alongside, same era.
Fully non-autoregressive neural machine translation: Tricks of the trade
Gu, J. and Kong, X · 2021
Later among the works it cites.
Deep encoder, shallow decoder: Reevaluating non-autoregressive machine translation
Kasai, J., Pappas, N., Peng, H., Cross, J., and Smith, N. A · 2021
Later among the works it cites.
Glancing transformer for non-autoregressive neural machine translation
Qian, L., Zhou, H., Bao, Y., Wang, M., Qiu, L., Zhang, W., Yu, Y., and Li, L · 2021
Later among the works it cites.
Guiding non-autoregressive neural machine translation decoding with reordering information
Ran, Q., Lin, Y., Li, P., and Zhou, J · 2021
Later among the works it cites.
Sequence-level training for non-autoregressive neural machine translation
Shao, C., Feng, Y., Zhang, J., Meng, F., and Zhou, J · 2021
Later among the works it cites.
Pos-constrained parallel decoding for non-autoregressive generation
Yang, K., Lei, W., Liu, D., Qi, W., and Lv, J · 2021
Later among the works it cites.
latent-glat: Glancing at latent variables for parallel text generation
Bao, Y., Zhou, H., Huang, S., Wang, D., Qian, L., Dai, X., Chen, J., and Li, L · 2022
Closest in time.
Non-autoregressive translation with layer-wise prediction and deep supervision
Huang, C., Zhou, H., Zaïane, O. R., Mou, L., and Li, L · 2022
Closest in time.
Directed acyclic transformer for non-autoregressive machine translation
Huang, F., Zhou, H., Liu, Y., Li, H., and Huang, M · 2022
Closest in time.