Zobrazeno 1 - 10
of 78
pro vyhledávání: '"NIU Fuqiang"'
Publikováno v:
Haiyang Kaifa yu guanli, Vol 41, Iss 5, Pp 138-145 (2024)
Underwater pile driving is a common operational method in engineering projects such as offshore bridges and offshore wind farms, and the impact of underwater noise on the marine ecological environment has attracted increasing attention. This paper an
Externí odkaz:
https://doaj.org/article/30c62ffbb08644a0b98e30a24cf5a964
Idioms represent a ubiquitous vehicle for conveying sentiments in the realm of everyday discourse, rendering the nuanced analysis of idiom sentiment crucial for a comprehensive understanding of emotional expression within real-world texts. Neverthele
Externí odkaz:
http://arxiv.org/abs/2409.17588
Autor:
Zhang, Bowen, Dai, Genan, Niu, Fuqiang, Yin, Nan, Fan, Xiaomao, Wang, Senzhang, Cao, Xiaochun, Huang, Hu
In modern digital environments, users frequently express opinions on contentious topics, providing a wealth of information on prevailing attitudes. The systematic analysis of these opinions offers valuable insights for decision-making in various sect
Externí odkaz:
http://arxiv.org/abs/2409.15690
Autor:
Niu, Fuqiang, Cheng, Zebang, Fu, Xianghua, Peng, Xiaojiang, Dai, Genan, Chen, Yin, Huang, Hu, Zhang, Bowen
Stance detection, which aims to identify public opinion towards specific targets using social media data, is an important yet challenging task. With the proliferation of diverse multimodal social media content including text, and images multimodal st
Externí odkaz:
http://arxiv.org/abs/2409.00597
This paper presents our winning submission to Subtask 2 of SemEval 2024 Task 3 on multimodal emotion cause analysis in conversations. We propose a novel Multimodal Emotion Recognition and Multimodal Emotion Cause Extraction (MER-MCE) framework that i
Externí odkaz:
http://arxiv.org/abs/2404.00511
Publikováno v:
LREC-COLING 2024
Previous stance detection studies typically concentrate on evaluating stances within individual instances, thereby exhibiting limitations in effectively modeling multi-party discussions concerning the same specific topic, as naturally transpire in au
Externí odkaz:
http://arxiv.org/abs/2403.11145
Autor:
Ni, Shiwen, Tan, Minghuan, Bai, Yuelin, Niu, Fuqiang, Yang, Min, Zhang, Bowen, Xu, Ruifeng, Chen, Xiaojun, Li, Chengming, Hu, Xiping, Li, Ye, Fan, Jianping
Publikováno v:
LREC-COLING 2024
Large language models (LLMs) have demonstrated impressive performance in various natural language processing (NLP) tasks. However, there is limited understanding of how well LLMs perform in specific domains (e.g, the intellectual property (IP) domain
Externí odkaz:
http://arxiv.org/abs/2402.16389
Autor:
Niu, Fuqiang a, 1, Liu, Zihan b, 1, Bai, Jianfang b, 1, Liu, Yongjie b, Yuan, Shaohua b, Zhai, Nuo b, Geng, Qiang a, Hu, Lingling a, Zhang, Li a, Gao, Xiaoran a, Liu, Jinke a, Zhao, Changping b, ⁎, Zhang, Liping b, ⁎, Song, Xiyue a, ⁎
Publikováno v:
In International Journal of Biological Macromolecules January 2025 285
Autor:
Niu, Fuqiang1 (AUTHOR), Liu, Zihan2 (AUTHOR), Liu, Yongjie2 (AUTHOR), Bai, Jianfang2 (AUTHOR), Zhang, Tianbao2 (AUTHOR), Yuan, Shaohua2 (AUTHOR), Bai, Xiucheng2 (AUTHOR), Zhao, Changping2 (AUTHOR), Zhang, Fengting2 (AUTHOR), Sun, Hui2 (AUTHOR) Sunhui628@sina.com, Zhang, Liping2 (AUTHOR) lpzhang8@126.com, Song, Xiyue1 (AUTHOR) songxiyue@nwafu.edu.cn
Publikováno v:
BMC Genomics. 7/30/2024, Vol. 25 Issue 1, p1-16. 16p.
Publikováno v:
In Plant Science November 2022 324