量被毁坏
发表于 2025-3-23 11:50:21
http://reply.papertrans.cn/47/4615/461486/461486_11.png
含糊
发表于 2025-3-23 14:50:44
http://reply.papertrans.cn/47/4615/461486/461486_12.png
巩固
发表于 2025-3-23 21:27:10
s is expensive. Existing models address this issue by code-switched data augmentation or intermediate fine-tuning of multilingual pre-trained models. However, these models can only perform implicit alignment across languages. In this paper, we propose a novel model named .ontrastive .earning for .ro
tackle
发表于 2025-3-23 23:31:06
Minhao Xue,Li Wang,Jie Shen,Kangning Wang,Wanning Wu,Long Fu has focused on predicting entity information after fusing visual and text features. However, pre-training language models have already acquired vast amounts of knowledge during their pre-training process. To leverage this knowledge, we propose a prompt network for MNER tasks (P-MNER). To minimize t
巫婆
发表于 2025-3-24 03:07:09
http://reply.papertrans.cn/47/4615/461486/461486_15.png
得罪人
发表于 2025-3-24 07:51:22
http://reply.papertrans.cn/47/4615/461486/461486_16.png
Decline
发表于 2025-3-24 13:18:55
Graph Network (GN) and Question Decomposition (QD) are two common approaches at present. The former uses the “black-box” reasoning process to capture the potential relationship between entities and sentences, thus achieving good performance. At the same time, the latter provides a clear reasoning lo
conscience
发表于 2025-3-24 15:46:39
Xingjian Zhang,Shaohuai Yu,Xinghua Li,Shuang Li,Zhenyu Tanfirst. This paper analyzed English-Chinese MT errors from the perspective of naming-telling clause (NT clause, hereafter). Two types of text were input to get the MT output: one was to input the whole original English sentences into an MT engine; the other was to parse English sentences into English
originality
发表于 2025-3-24 23:04:30
http://reply.papertrans.cn/47/4615/461486/461486_19.png
BRACE
发表于 2025-3-25 03:13:13
http://reply.papertrans.cn/47/4615/461486/461486_20.png