Bayesian Iterative Prediction and Lexical-based Interpretation for Disturbed Chinese Sentence Pair Matching

Author:

Guo Muzhe1ORCID,Guo Muhao2ORCID,Su Juntao1ORCID,Chen Junyu1ORCID,Yu Jiaqian1ORCID,Wang Jiaqi3ORCID,Du Hongfei1ORCID,Sahu Parmanand4ORCID,Sharma Ashwin Assysh5ORCID,Jin Fang1ORCID

Affiliation:

1. George Washington University, Washington, DC, USA

2. Arizona State University, Tempe, AZ, USA

3. Alibaba Group, Hangzhou, Zhejiang, China

4. The University of Texas at Dallas, Richardson, TX, USA

5. University of Minnesota Twin-Cities, Minneapolis, MN, USA

Publisher

ACM

Reference47 articles.

1. Julius Adebayo, Justin Gilmer, Michael Muelly, Ian Goodfellow, Moritz Hardt, and Been Kim. 2018. Sanity checks for saliency maps. Advances in neural information processing systems , Vol. 31 (2018).

2. Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, and Himabindu Lakkaraju. 2021. Towards the unification and robustness of perturbation and gradient based explanations. In International Conference on Machine Learning. PMLR, 110--119.

3. Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014).

4. Charles Blundell, Julien Cornebise, Koray Kavukcuoglu, and Daan Wierstra. 2015. Weight uncertainty in neural network. In International conference on machine learning. PMLR, 1613--1622.

5. Pre-Training With Whole Word Masking for Chinese BERT

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