On the Inference Calibration of Neural Machine Translation
暂无分享,去创建一个
Shuming Shi | Zhaopeng Tu | Yang Liu | Shuo Wang | Zhaopeng Tu | Yang Liu | Shuming Shi | Shuo Wang
[1] Marc'Aurelio Ranzato,et al. Sequence Level Training with Recurrent Neural Networks , 2015, ICLR.
[2] Matthew G. Snover,et al. A Study of Translation Edit Rate with Targeted Human Annotation , 2006, AMTA.
[3] Brendan T. O'Connor,et al. Posterior calibration and exploratory analysis for natural language processing models , 2015, EMNLP.
[4] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[5] L. Deng,et al. Calibration of Confidence Measures in Speech Recognition , 2011, IEEE Transactions on Audio, Speech, and Language Processing.
[6] Salim Roukos,et al. Bleu: a Method for Automatic Evaluation of Machine Translation , 2002, ACL.
[7] Noah A. Smith,et al. A Simple, Fast, and Effective Reparameterization of IBM Model 2 , 2013, NAACL.
[8] Sergey Ioffe,et al. Rethinking the Inception Architecture for Computer Vision , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Percy Liang,et al. Calibrated Structured Prediction , 2015, NIPS.
[10] Lijun Wu,et al. Beyond Error Propagation in Neural Machine Translation: Characteristics of Language Also Matter , 2018, EMNLP.
[11] Ralph Weischedel,et al. A STUDY OF TRANSLATION ERROR RATE WITH TARGETED HUMAN ANNOTATION , 2005 .
[12] Xiaoqian Jiang,et al. Predicting accurate probabilities with a ranking loss , 2012, ICML.
[13] Yang Liu,et al. Neural Machine Translation with Reconstruction , 2016, AAAI.
[14] Kilian Q. Weinberger,et al. On Calibration of Modern Neural Networks , 2017, ICML.
[15] Geoffrey E. Hinton,et al. When Does Label Smoothing Help? , 2019, NeurIPS.
[16] Yoshua Bengio,et al. Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.
[17] Nitish Srivastava,et al. Improving neural networks by preventing co-adaptation of feature detectors , 2012, ArXiv.
[18] Leon Wenliang Zhong,et al. Accurate Probability Calibration for Multiple Classifiers , 2013, IJCAI.
[19] John Platt,et al. Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likelihood Methods , 1999 .
[20] Shu-Tao Xia,et al. Adaptive Regularization of Labels , 2019, ArXiv.
[21] Rico Sennrich,et al. Neural Machine Translation of Rare Words with Subword Units , 2015, ACL.
[22] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[23] Rich Caruana,et al. Predicting good probabilities with supervised learning , 2005, ICML.
[24] Milos Hauskrecht,et al. Obtaining Well Calibrated Probabilities Using Bayesian Binning , 2015, AAAI.
[25] Jingbo Zhu,et al. Learning Deep Transformer Models for Machine Translation , 2019, ACL.
[26] Sunita Sarawagi,et al. Calibration of Encoder Decoder Models for Neural Machine Translation , 2019, ArXiv.
[27] Bianca Zadrozny,et al. Transforming classifier scores into accurate multiclass probability estimates , 2002, KDD.
[28] Huanbo Luan,et al. Improving Back-Translation with Uncertainty-based Confidence Estimation , 2019, EMNLP.
[29] Marc'Aurelio Ranzato,et al. Analyzing Uncertainty in Neural Machine Translation , 2018, ICML.