Zobrazeno 1 - 10
of 7 169
pro vyhledávání: '"AI agent"'
Artificial General Intelligence (AGI), widely regarded as the fundamental goal of artificial intelligence, represents the realization of cognitive capabilities that enable the handling of general tasks with human-like proficiency. Researchers in brai
Externí odkaz:
http://arxiv.org/abs/2412.08875
As financial markets grow increasingly complex, there is a rising need for automated tools that can effectively assist human analysts in equity research, particularly within sell-side research. While Generative AI (GenAI) has attracted significant at
Externí odkaz:
http://arxiv.org/abs/2411.08804
Classroom dialogue plays a crucial role in fostering student engagement and deeper learning. However, analysing dialogue sequences has traditionally relied on either theoretical frameworks or empirical descriptions of practice, with limited integrati
Externí odkaz:
http://arxiv.org/abs/2411.08418
Autor:
Berdoz, Frédéric, Wattenhofer, Roger
While autonomous agents often surpass humans in their ability to handle vast and complex data, their potential misalignment (i.e., lack of transparency regarding their true objective) has thus far hindered their use in critical applications such as s
Externí odkaz:
http://arxiv.org/abs/2412.00033
In recent years, the application of generative artificial intelligence (GenAI) in financial analysis and investment decision-making has gained significant attention. However, most existing approaches rely on single-agent systems, which fail to fully
Externí odkaz:
http://arxiv.org/abs/2411.04788
As AI closely interacts with human society, it is crucial to ensure that its decision-making is safe, altruistic, and aligned with human ethical and moral values. However, existing research on embedding ethical and moral considerations into AI remain
Externí odkaz:
http://arxiv.org/abs/2410.21882
We design and demonstrate the first field trial of LLM-powered AI Agent for ADON. Three operation modes of the Agent are proposed for network lifecycle management. The Agent efficiently processes wavelength add/drop and soft/hard failures, and achiev
Externí odkaz:
http://arxiv.org/abs/2409.14605
Autor:
Zhang, Jianguo, Lan, Tian, Zhu, Ming, Liu, Zuxin, Hoang, Thai, Kokane, Shirley, Yao, Weiran, Tan, Juntao, Prabhakar, Akshara, Chen, Haolin, Liu, Zhiwei, Feng, Yihao, Awalgaonkar, Tulika, Murthy, Rithesh, Hu, Eric, Chen, Zeyuan, Xu, Ran, Niebles, Juan Carlos, Heinecke, Shelby, Wang, Huan, Savarese, Silvio, Xiong, Caiming
Autonomous agents powered by large language models (LLMs) have attracted significant research interest. However, the open-source community faces many challenges in developing specialized models for agent tasks, driven by the scarcity of high-quality
Externí odkaz:
http://arxiv.org/abs/2409.03215
Autor:
Yu, Yi, Yao, Shengyue, Zhou, Tianchen, Fu, Yexuan, Yu, Jingru, Wang, Ding, Wang, Xuhong, Chen, Cen, Lin, Yilun
In the digital era, data has become a pivotal asset, advancing technologies such as autonomous driving. Despite this, data trading faces challenges like the absence of robust pricing methods and the lack of trustworthy trading mechanisms. To address
Externí odkaz:
http://arxiv.org/abs/2407.00995
Autor:
Zhang, Jingyue, Arawjo, Ian
As large language models (LLMs) advance, their potential applications have grown significantly. However, it remains difficult to evaluate LLM behavior on user-specific tasks and craft effective pipelines to do so. Many users struggle with where to st
Externí odkaz:
http://arxiv.org/abs/2409.13588