Zobrazeno 1 - 10
of 111
pro vyhledávání: '"Yang, Yizhe"'
The recent success of large language models (LLMs) has attracted widespread interest to develop role-playing conversational agents personalized to the characteristics and styles of different speakers to enhance their abilities to perform both general
Externí odkaz:
http://arxiv.org/abs/2405.10150
Autor:
Ying, Jiahao, Cao, Yixin, Bai, Yushi, Sun, Qianru, Wang, Bo, Tang, Wei, Ding, Zhaojun, Yang, Yizhe, Huang, Xuanjing, Yan, Shuicheng
Large language models (LLMs) have achieved impressive performance across various natural language benchmarks, prompting a continual need to curate more difficult datasets for larger LLMs, which is costly and time-consuming. In this paper, we propose
Externí odkaz:
http://arxiv.org/abs/2402.11894
Knowledge-grounded dialogue is a task of generating an informative response based on both the dialogue history and external knowledge source. In general, there are two forms of knowledge: manually annotated knowledge graphs and knowledge text from we
Externí odkaz:
http://arxiv.org/abs/2312.07868
Language style is necessary for AI systems to understand and generate diverse human language accurately. However, previous text style transfer primarily focused on sentence-level data-driven approaches, limiting exploration of potential problems in l
Externí odkaz:
http://arxiv.org/abs/2311.08389
Autor:
Yang, Yizhe, Sun, Huashan, Li, Jiawei, Liu, Runheng, Li, Yinghao, Liu, Yuhang, Huang, Heyan, Gao, Yang
Large Language Models (LLMs) have demonstrated remarkable performance across various natural language tasks, marking significant strides towards general artificial intelligence. While general artificial intelligence is leveraged by developing increas
Externí odkaz:
http://arxiv.org/abs/2310.15777
The knowledge-grounded dialogue task aims to generate responses that convey information from given knowledge documents. However, it is a challenge for the current sequence-based model to acquire knowledge from complex documents and integrate it to pe
Externí odkaz:
http://arxiv.org/abs/2204.12681
Multi-hop Question Answering (QA) requires the machine to answer complex questions by finding scattering clues and reasoning from multiple documents. Graph Network (GN) and Question Decomposition (QD) are two common approaches at present. The former
Externí odkaz:
http://arxiv.org/abs/2203.09073
Publikováno v:
In Tourism Management Perspectives September 2024 53
Publikováno v:
In Knowledge-Based Systems 15 August 2024 298
Autor:
Liu, Qingping, Niu, Yong, Pei, Zijie, Yang, Yizhe, Xie, Yujia, Wang, Mengruo, Wang, Jingyuan, Wu, Mengqi, Zheng, Jie, Yang, Peihao, Hao, Haiyan, Pang, Yaxian, Bao, Lei, Dai, Yufei, Niu, Yujie, Zhang, Rong
Publikováno v:
In Journal of Hazardous Materials 5 August 2024 474