Titlebook: Image and Graphics; 9th International Co Yao Zhao,Xiangwei Kong,David Taubman Conference proceedings 2017 Springer Nature Switzerland AG 20

Yourself

Jiayu Dong,Huicheng Zheng,Lina Liannd self-attention within input sequence, where the input sequence contains a current question and a passage. Then a feature selection method is designed to enhance the useful history turns of conversation and weaken the unnecessary information. Finally, we demonstrate the effectiveness of the propos

垫子

Long Zhang,Jieyu Zhao,Xiangfu Shi,Xulun Yeith the NER model to fuse both contexts and dictionary knowledge into NER. Extensive experiments on the CoNLL-2003 benchmark dataset validate the effectiveness of our approach in exploiting entity dictionaries to improve the performance of various NER models.

洞穴

enlist

Yang Yu,Zhiqiang Gong,Ping Zhong,Jiaxin Shannd self-attention within input sequence, where the input sequence contains a current question and a passage. Then a feature selection method is designed to enhance the useful history turns of conversation and weaken the unnecessary information. Finally, we demonstrate the effectiveness of the propos

庄严

外表读作

dermatomyositis

Jing Wang,Hong Zhu,Shan Xue,Jing Shipairs. In the interaction layer, we initially fuse the information of the sentence pairs to obtain low-level semantic information; at the same time, we use the bi-directional attention in the machine reading comprehension model and self-attention to obtain the high-level semantic information. We use

过于光泽

Collected

样式

Wei Hu,Hongyu Qi,Zhenbing Zhao,Leilei Xuction strategies to explore its effect. We conduct experiments on seven Semantic Textual Similarity (STS) tasks. The experimental results show that our ConIsI models based on . and . achieve state-of-the-art performance, substantially outperforming previous best models SimCSE-. and SimCSE-. by 2.05%