Zobrazeno 1 - 10
of 119
pro vyhledávání: '"Chen, Guizhen"'
Autor:
Ding, Bosheng, Qin, Chengwei, Zhao, Ruochen, Luo, Tianze, Li, Xinze, Chen, Guizhen, Xia, Wenhan, Hu, Junjie, Luu, Anh Tuan, Joty, Shafiq
In the rapidly evolving field of large language models (LLMs), data augmentation (DA) has emerged as a pivotal technique for enhancing model performance by diversifying training examples without the need for additional data collection. This survey ex
Externí odkaz:
http://arxiv.org/abs/2403.02990
Large language models (LLMs) have demonstrated impressive capabilities across diverse languages. This study explores how LLMs handle multilingualism. Based on observed language ratio shifts among layers and the relationships between network structure
Externí odkaz:
http://arxiv.org/abs/2402.18815
Despite the success of chain of thought in enhancing language model reasoning, the underlying process remains less well understood. Although logically sound reasoning appears inherently crucial for chain of thought, prior studies surprisingly reveal
Externí odkaz:
http://arxiv.org/abs/2311.09277
Computational argumentation has become an essential tool in various domains, including law, public policy, and artificial intelligence. It is an emerging research field in natural language processing that attracts increasing attention. Research on co
Externí odkaz:
http://arxiv.org/abs/2311.09022
Instruction tuning has become an essential process for optimizing the performance of large language models (LLMs). However, current text-to-text instruction tuning methods, referred to as TextTuning, exhibit significant limitations in terms of genera
Externí odkaz:
http://arxiv.org/abs/2310.02953
Autor:
Chia, Yew Ken, Chen, Hui, Han, Wei, Chen, Guizhen, Aljunied, Sharifah Mahani, Poria, Soujanya, Bing, Lidong
Aspect Sentiment Triplet Extraction (ASTE) is a subtask of Aspect-Based Sentiment Analysis (ABSA) that considers each opinion term, their expressed sentiment, and the corresponding aspect targets. However, existing methods are limited to the in-domai
Externí odkaz:
http://arxiv.org/abs/2305.14434
Autor:
Liu, Chaoqun, Zhang, Wenxuan, Chen, Guizhen, Wu, Xiaobao, Luu, Anh Tuan, Chang, Chip Hong, Bing, Lidong
Existing solutions to zero-shot text classification either conduct prompting with pre-trained language models, which is sensitive to the choices of templates, or rely on large-scale annotated data of relevant tasks for meta-tuning. In this work, we p
Externí odkaz:
http://arxiv.org/abs/2305.11442
Autor:
Li, Liangliang, Sui, Yuzhen, Li, Xinmiao, Song, Pengtao, Chen, Guizhen, Liu, Hu, Zuo, Shoujun, Guo, Jinjie, Wang, Qiong, Sun, Qiyuan, Dai, Hongyu, Li, Junqiang, Zhang, Tao, Liu, Fang, Zhang, Longxian, Dong, Haiju
Publikováno v:
In Acta Tropica June 2024 254
Autor:
Sui, Yuzhen, Song, Pengtao, Chen, Guizhen, Zuo, Shoujun, Liu, Hu, Guo, Jinjie, Chang, Zhihai, Dai, Hongyu, Liu, Fang, Dong, Haiju
Publikováno v:
In Preventive Veterinary Medicine May 2024 226
Autor:
Fu, Mengyue, Xu, Rui, Chen, Guizhen, Zheng, Xuemei, Shu, Bin, Huang, He, Duan, Guangyou, Chen, Yuanjing
Publikováno v:
In Heliyon 15 February 2024 10(3)