no code implementations • Findings (EMNLP) 2021 • Jiawei Wang, Hai Zhao, Yinggong Zhao, Libin Shen
Machine reading comprehension (MRC) is a challenging NLP task for it requires to carefully deal with all linguistic granularities from word, sentence to passage.
Chinese Reading Comprehension Machine Reading Comprehension +1
no code implementations • EMNLP 2020 • Chengyue Jiang, Yinggong Zhao, Shanbo Chu, Libin Shen, Kewei Tu
On the other hand, symbolic rules such as regular expressions are interpretable, require no training, and often achieve decent accuracy; but rules cannot benefit from labeled data when available and hence underperform neural networks in rich-resource scenarios.
1 code implementation • ACL 2022 • Yilin Zhao, Hai Zhao, Libin Shen, Yinggong Zhao
As a broad and major category in machine reading comprehension (MRC), the generalized goal of discriminative MRC is answer prediction from the given materials.
no code implementations • 10 Mar 2022 • Xuanwei Zhang, Libin Shen, Disheng Pan, Liang Wang, Yanjun Miao
We deploy a backward decoder which can act as an effective regularization method to the forward decoder.
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Chengyue Jiang, Zhonglin Nian, Kaihao Guo, Shanbo Chu, Yinggong Zhao, Libin Shen, Kewei Tu
Numeral embeddings represented in this manner can be plugged into existing word embedding learning approaches such as skip-gram for training.
no code implementations • 26 Apr 2020 • Xiaoqing Geng, Xiwen Chen, Kenny Q. Zhu, Libin Shen, Yinggong Zhao
In this framework, models not only strive to classify query instances, but also seek underlying knowledge about the support instances to obtain better instance representations.
no code implementations • 28 Dec 2019 • Chengyue Jiang, Zhonglin Nian, Kaihao Guo, Shanbo Chu, Yinggong Zhao, Libin Shen, Kewei Tu
Numeral embeddings represented in this manner can be plugged into existing word embedding learning approaches such as skip-gram for training.