AOS-Bench: Can LLM Agents Manage Dynamic Workloads?
arXiv:2610.33178v1 Announce Type: new Abstract: Coding agents are moving from handling one request at a time to serving as persistent assistants to which users hand a stream of work: a build, a data-processing job and a bug fix may all be pending on the same machine at once. Such an agent must decide when to take on new tasks, how to delegate and overlap them, and how to stay within the machine's CPU and memory. Existing benchmarks cannot measure this, because they evaluate each task in isolation. We introduce \benchname{}, which evaluates an agent system as a workload manager: verified tasks
阅读原文 · arXiv 人工智能本文由 SoccerDream AI 自动聚合索引，内容版权归原作者与 arXiv 人工智能 所有。
本站仅作技术动态聚合，不构成任何形式的建议。
本站仅作技术动态聚合，不构成任何形式的建议。