March 26, 2024, 4:51 a.m. | Kai Mei, Zelong Li, Shuyuan Xu, Ruosong Ye, Yingqiang Ge, Yongfeng Zhang

cs.CL updates on arXiv.org arxiv.org

arXiv:2403.16971v1 Announce Type: cross
Abstract: The integration and deployment of large language model (LLM)-based intelligent agents have been fraught with challenges that compromise their efficiency and efficacy. Among these issues are sub-optimal scheduling and resource allocation of agent requests over the LLM, the difficulties in maintaining context during interactions between agent and LLM, and the complexities inherent in integrating heterogeneous agents with different capabilities and specializations. The rapid increase of agent quantity and complexity further exacerbates these issues, often leading …

agent arxiv cs.ai cs.cl cs.os llm operating system type

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