新闻
WorkflowArena: Benchmarking Executable Workflow Orchestration in LLM-Based Multi-Agent Systems
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- WorkflowArena benchmark evaluates how LLM agents autonomously organize multi-agent workflows across 145 tasks in eight professional domains.
- 为何重要
- Engineers building multi-agent systems need to assess whether models can effectively delegate work and structure task execution without predefined workflows.
- 注意
- No single model configuration excels across all domains; workflow quality varies significantly by model and task type, requiring domain-specific evaluation.
- agent
- llm
- language model
- multi-agent
- eval
这条新闻背后的模式
- Agentic Context Engineering (Evolving Playbook)
- MMAU: Massive Multitask Agent Understanding
- Task Management & Orchestration
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
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