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It is well believed that the higher uncertainty in a word of the caption, the more inter-correlated context information is required to determine it.
Exploring uncertainty measures for image-caption embedding-and-retrieval task
Hama, K.; Matsubara, T.; Uehara, K.; and Cai, J. 2019 · 1904
Earlier work this paper cites.
Masked Non-Autoregressive Image Captioning
Gao, J.; Meng, X.; Wang, S.; Li, X.; Wang, S.; Ma, S.; and Gao, W. 2019 · 1906
Earlier work this paper cites.
Imitation learning for non-autoregressive neural machine translation
Wei, B.; Wang, M.; Zhou, H.; Lin, J.; Xie, J.; and Sun, X. 2019 · 1906
Earlier work this paper cites.
Fast Image Caption Generation with Position Alignment
Fei, Z.-c. 2019 · 1912
Earlier work this paper cites.
Semantics-preserving bag-of-words models and applications
Wu, L.; Hoi, S. C.; and Yu, N. 2010 · 1920
Earlier work this paper cites.
Semi-autoregressive training improves mask-predict decoding
Ghazvininejad, M.; Levy, O.; and Zettlemoyer, L. 2020 · 2001
Earlier work this paper cites.
BLEU: a Method for Automatic Evaluation of Machine Translation
Papineni, K.; Roukos, S.; Ward, T.; and Zhu, W. J. 2002 · 2002
Earlier work this paper cites.
Efficient algorithms for the maximum subarray problem by distance matrix multiplication
Takaoka, T. 2002 · 2002
Earlier work this paper cites.
ROUGE: A Package for Automatic Evaluation of summaries
Lin, C.-Y. 2004 · 2004
Earlier work this paper cites.
Non-Autoregressive Image Captioning with Counterfactuals-Critical Multi-Agent Learning
Guo, L.; Liu, J.; Zhu, X.; He, X.; Jiang, J.; and Lu, H. 2020 · 2005
Earlier work this paper cites.
POINTER: Constrained progressive text generation via insertion-based generative pre-training
Zhang, Y.; Wang, G.; Li, C.; Gan, Z.; Brockett, C.; and Dolan, B. 2020 · 2005
Earlier work this paper cites.
METEOR: An automatic metric for MT evaluation with high levels of correlation with human judgments
Lavie, A.; and Agarwal, A. 2007 · 2007
Earlier work this paper cites.
Understanding bag-of-words model: a statistical framework
Zhang, Y.; Jin, R.; and Zhou, Z.-H. 2010 · 2010
Earlier work this paper cites.
Adam: A method for stochastic optimization
Kingma, D. P.; and Ba, J. 2014 · 2014
Earlier work this paper cites.
Microsoft coco captions: Data collection and evaluation server
Chen, X.; Fang, H.; Lin, T.-Y.; Vedantam, R.; Gupta, S.; Dollár, P.; and Zitnick, C. L. 2015 · 2015
Earlier work this paper cites.
Deep visual-semantic alignments for generating image descriptions
Karpathy, A.; and Fei-Fei, L. 2015 · 2015
Earlier work this paper cites.
Linear programming , volume 3
Vanderbei, R. J.; et al. 2015 · 2015
Earlier work this paper cites.
Cider: Consensus-based image description evaluation
Vedantam, R.; Lawrence Zitnick, C.; and Parikh, D. 2015 · 2015
Cited alongside, same era.
Show and tell: A neural image caption generator
Vinyals, O.; Toshev, A.; Bengio, S.; and Erhan, D. 2015 · 2015
Cited alongside, same era.
SPICE: Semantic Propositional Image Caption Evaluation
Anderson, P.; Fernando, B.; Johnson, M.; and Gould, S. 2016 · 2016
Cited alongside, same era.
Self-Critical Sequence Training for Image Captioning
Rennie, S. J.; Marcheret, E.; Mroueh, Y.; Ross, J.; and Goel, V. 2017 · 2017
Cited alongside, same era.
Attention Is All You Need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, L.; and Polosukhin, I. 2017 · 2017
Cited alongside, same era.
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
Anderson, P.; He, X.; Buehler, C.; Teney, D.; Johnson, M.; Gould, S.; and Zhang, L. 2018 · 2018
Imputer: Sequence modelling via imputation and dynamic programming
Chan, W.; Saharia, C.; Hinton, G.; Norouzi, M.; and Jaitly, N. 2020 · 2020
Later among the works it cites.
Meshed-Memory Transformer for Image Captioning
Cornia, M.; Stefanini, M.; Baraldi, L.; and Cucchiara, R. 2020 · 2020
Later among the works it cites.
Iterative Back Modification for Faster Image Captioning
Fei, Z. 2020 · 2020
Later among the works it cites.
In defense of grid features for visual question answering
Jiang, H.; Misra, I.; Rohrbach, M.; Learned-Miller, E.; and Chen, X. 2020 · 2020
Later among the works it cites.
X-linear attention networks for image captioning
Pan, Y.; Yao, T.; Li, Y.; and Mei, T. 2020 · 2020
Later among the works it cites.
Blank Language Model: flexible sequence modeling by any-order generation
Quach, V. 2020 · 2020
Later among the works it cites.
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Cited alongside, same era.
Non-Autoregressive Neural Machine Translation
Gu, J.; Bradbury, J.; Xiong, C.; Li, V. O. K.; and Socher, R. 2018 · 2018
Cited alongside, same era.
Uncertainty-aware attention for reliable interpretation and prediction
Heo, J.; Lee, H. B.; Kim, S.; Lee, J.; Kim, K. J.; Yang, E.; and Hwang, S. J. 2018 · 2018
Cited alongside, same era.
Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement
Jason, L.; Elman, M.; Neubig, G.; and Kyunghyun, C. 2018 · 2018
Cited alongside, same era.
Uncertainty aware AI ML: why and how
Kaplan, L.; Cerutti, F.; Sensoy, M.; Preece, A.; and Sullivan, P. 2018 · 2018
Cited alongside, same era.
Semi-autoregressive neural machine translation
Wang, C.; Zhang, J.; and Chen, H. 2018 · 2018
Cited alongside, same era.
Exploring Visual Relationship for Image Captioning
Yao, T.; Pan, Y.; Li, Y.; and Mei, T. 2018 · 2018
Cited alongside, same era.
Uncertainty-aware curriculum learning for neural machine translation
Zhou, Y.; Yang, B.; Wong, D. F.; Wan, Y.; and Chao, L. S. 2020 · 2020
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Non-autoregressive image captioning with counterfactuals-critical multi-agent learning
Guo, L.; Liu, J.; Zhu, X.; He, X.; Jiang, J.; and Lu, H. 2021 · 2021
Later among the works it cites.
From show to tell: A survey on image captioning
Stefanini, M.; Cornia, M.; Baraldi, L.; Cascianelli, S.; Fiameni, G.; and Cucchiara, R. 2021 · 2021
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Semi-Autoregressive Image Captioning
Yan, X.; Fei, Z.; Li, Z.; Wang, S.; Huang, Q.; and Tian, Q. 2021 · 2021
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RSTNet: Captioning with adaptive attention on visual and non-visual words
Zhang, X.; Sun, X.; Luo, Y.; Ji, J.; Zhou, Y.; Wu, Y.; Huang, F.; and Ji, R. 2021 · 2021
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Semi-autoregressive transformer for image captioning
Zhou, Y.; Zhang, Y.; Hu, Z.; and Wang, M. 2021 · 2021
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Attention-Aligned Transformer for Image Captioning
Fei, Z. 2022 · 2022
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Comprehending and Ordering Semantics for Image Captioning
Li, Y.; Pan, Y.; Yao, T.; and Mei, T. 2022 · 2022
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DIFNet: Boosting Visual Information Flow for Image Captioning
Wu, M.; Zhang, X.; Sun, X.; Zhou, Y.; Chen, C.; Gu, J.; Sun, X.; and Ji, R. 2022 · 2022
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Reformer: The relational transformer for image captioning
Yang, X.; Liu, Y.; and Wang, X. 2022 · 2022
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Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Xu, K.; Ba, J.; Kiros, R.; Cho, K.; Courville, A.; Salakhutdinov, R.; Zemel, R.; and Bengio, Y. 2015 · 2057
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