新闻
Argo-Bench: Evaluating Data Agents on Enterprise-Scale Workflows
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Argo-Bench is a benchmark with 210 tasks evaluating AI agents on realistic enterprise data warehouse workflows across 235 tables and 7.5 billion rows.
- 为何重要
- Matters for engineers building data agents or evaluating LLMs on complex SQL and business logic tasks requiring multi-table reasoning and real-world consequences.
- 注意
- Best models score 95 or higher on only 35% of tasks, averaging 59.5 points, suggesting current agents struggle significantly with enterprise-scale data navigation and decision-making.
- agent
- reasoning
- eval
- benchmark
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