新闻
OmegaUse-OfficeVal: Benchmarking LLM Agents on Long-Horizon Office-Suite Tasks with Economic Grounding
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Researchers released OmegaUse-OfficeVal, a benchmark with 100 office-suite tasks paired with human labor time and cost data to evaluate LLM agent performance.
- 为何重要
- Engineering teams building or deploying LLM agents need this to understand whether automation saves money and delivers quality comparable to human workers.
- 注意
- All tested LLMs remain cheaper and faster than humans but have not yet matched human-level deliverable quality on these complex tasks.
- agent
- llm
- language model
- rag
- serving
这条新闻背后的模式
每个模式都讲清楚技术如何运作、何时值得投入，以及在哪里会失效。
The Agent Architect
每周一个模式、一个权衡、一个生产事故案例。为构建智能体系统的人准备的每周简报。
每周一封邮件,一键退订。您的地址仅用于发送简报。