Zobrazeno 1 - 10
of 287
pro vyhledávání: '"Shang Shuo"'
There are two issues in news-driven multi-stock movement prediction tasks that are not well solved in the existing works. On the one hand, "relation discovery" is a pivotal part when leveraging the price information of other stocks to achieve accurat
Externí odkaz:
http://arxiv.org/abs/2411.06391
Autor:
Wu, Qinzhuo, Xu, Weikai, Liu, Wei, Tan, Tao, Liu, Jianfeng, Li, Ang, Luan, Jian, Wang, Bin, Shang, Shuo
Recently, mobile AI agents based on VLMs have been gaining increasing attention. These works typically utilize VLM as a foundation, fine-tuning it with instruction-based mobile datasets. However, these VLMs are typically pre-trained on general-domain
Externí odkaz:
http://arxiv.org/abs/2409.14818
Autor:
Huang, Chengrui, Shi, Zhengliang, Wen, Yuntao, Chen, Xiuying, Han, Peng, Gao, Shen, Shang, Shuo
Tool learning methods have enhanced the ability of large language models (LLMs) to interact with real-world applications. Many existing works fine-tune LLMs or design prompts to enable LLMs to select appropriate tools and correctly invoke them to mee
Externí odkaz:
http://arxiv.org/abs/2407.03007
Autor:
Deng, Shihan, Xu, Weikai, Sun, Hongda, Liu, Wei, Tan, Tao, Liu, Jianfeng, Li, Ang, Luan, Jian, Wang, Bin, Yan, Rui, Shang, Shuo
With the remarkable advancements of large language models (LLMs), LLM-based agents have become a research hotspot in human-computer interaction. However, there is a scarcity of benchmarks available for LLM-based mobile agents. Benchmarking these agen
Externí odkaz:
http://arxiv.org/abs/2407.00993
Most economic theories typically assume that financial market participants are fully rational individuals and use mathematical models to simulate human behavior in financial markets. However, human behavior is often not entirely rational and is chall
Externí odkaz:
http://arxiv.org/abs/2406.19966
Autor:
Sun, Hongda, Lin, Hongzhan, Yan, Haiyu, Zhu, Chen, Song, Yang, Gao, Xin, Shang, Shuo, Yan, Rui
The emergence of online recruitment services has revolutionized the traditional landscape of job seeking and recruitment, necessitating the development of high-quality industrial applications to improve person-job fitting. Existing methods generally
Externí odkaz:
http://arxiv.org/abs/2405.18113
Recommendation systems play a crucial role in various domains, suggesting items based on user behavior.However, the lack of transparency in presenting recommendations can lead to user confusion. In this paper, we introduce Data-level Recommendation E
Externí odkaz:
http://arxiv.org/abs/2404.06311
Large language model agents have demonstrated remarkable advancements across various complex tasks. Recent works focus on optimizing the agent team or employing self-reflection to iteratively solve complex tasks. Since these agents are all based on t
Externí odkaz:
http://arxiv.org/abs/2404.05569
Autor:
Sun, Hongda, Liu, Yuxuan, Wu, Chengwei, Yan, Haiyu, Tai, Cheng, Gao, Xin, Shang, Shuo, Yan, Rui
Open-domain question answering (ODQA) has emerged as a pivotal research spotlight in information systems. Existing methods follow two main paradigms to collect evidence: (1) The \textit{retrieve-then-read} paradigm retrieves pertinent documents from
Externí odkaz:
http://arxiv.org/abs/2403.05217
Personalized dialogue systems have gained significant attention in recent years for their ability to generate responses in alignment with different personas. However, most existing approaches rely on pre-defined personal profiles, which are not only
Externí odkaz:
http://arxiv.org/abs/2403.03102