Zobrazeno 1 - 10
of 28
pro vyhledávání: '"yuan, Siyu"'
Autor:
Xu, Rui, Lu, Dakuan, Tan, Xiaoyu, Wang, Xintao, Yuan, Siyu, Chen, Jiangjie, Chu, Wei, Yinghui, Xu
Large language models~(LLMs) have demonstrated impressive performance in various applications, among which role-playing language agents (RPLAs) have engaged a broad user base. Now, there is a growing demand for RPLAs that represent Key Opinion Leader
Externí odkaz:
http://arxiv.org/abs/2407.05305
With the advent of 6G technology, the demand for efficient and intelligent systems in industrial applications has surged, driving the need for advanced solutions in target localization. Utilizing swarm robots to locate unknown targets involves naviga
Externí odkaz:
http://arxiv.org/abs/2406.19930
The rise of powerful large language models (LLMs) has spurred a new trend in building LLM-based autonomous agents for solving complex tasks, especially multi-agent systems. Despite the remarkable progress, we notice that existing works are heavily de
Externí odkaz:
http://arxiv.org/abs/2406.14228
Analogical reasoning plays a critical role in human cognition, enabling us to understand new concepts by associating them with familiar ones. Previous research in the AI community has mainly focused on identifying and generating analogies and then ex
Externí odkaz:
http://arxiv.org/abs/2406.11375
Multi-Modal Knowledge Graphs (MMKGs) have proven valuable for various downstream tasks. However, scaling them up is challenging because building large-scale MMKGs often introduces mismatched images (i.e., noise). Most entities in KGs belong to the lo
Externí odkaz:
http://arxiv.org/abs/2406.10902
Autor:
Yang, Ruihan, Chen, Jiangjie, Zhang, Yikai, Yuan, Siyu, Chen, Aili, Richardson, Kyle, Xiao, Yanghua, Yang, Deqing
Language agents powered by large language models (LLMs) are increasingly valuable as decision-making tools in domains such as gaming and programming. However, these agents often face challenges in achieving high-level goals without detailed instructi
Externí odkaz:
http://arxiv.org/abs/2406.04784
Autor:
Chen, Jiangjie, Wang, Xintao, Xu, Rui, Yuan, Siyu, Zhang, Yikai, Shi, Wei, Xie, Jian, Li, Shuang, Yang, Ruihan, Zhu, Tinghui, Chen, Aili, Li, Nianqi, Chen, Lida, Hu, Caiyu, Wu, Siye, Ren, Scott, Fu, Ziquan, Xiao, Yanghua
Recent advancements in large language models (LLMs) have significantly boosted the rise of Role-Playing Language Agents (RPLAs), i.e., specialized AI systems designed to simulate assigned personas. By harnessing multiple advanced abilities of LLMs, i
Externí odkaz:
http://arxiv.org/abs/2404.18231
Puns play a vital role in academic research due to their distinct structure and clear definition, which aid in the comprehensive analysis of linguistic humor. However, the understanding of puns in large language models (LLMs) has not been thoroughly
Externí odkaz:
http://arxiv.org/abs/2404.13599
Autor:
Yuan, Xinfeng, Yuan, Siyu, Cui, Yuhan, Lin, Tianhe, Wang, Xintao, Xu, Rui, Chen, Jiangjie, Yang, Deqing
Large language models (LLMs) have demonstrated impressive performance and spurred numerous AI applications, in which role-playing agents (RPAs) are particularly popular, especially for fictional characters. The prerequisite for these RPAs lies in the
Externí odkaz:
http://arxiv.org/abs/2404.12726
Autor:
Xu, Rui, Wang, Xintao, Chen, Jiangjie, Yuan, Siyu, Yuan, Xinfeng, Liang, Jiaqing, Chen, Zulong, Dong, Xiaoqing, Xiao, Yanghua
Can Large Language Models substitute humans in making important decisions? Recent research has unveiled the potential of LLMs to role-play assigned personas, mimicking their knowledge and linguistic habits. However, imitative decision-making requires
Externí odkaz:
http://arxiv.org/abs/2404.12138