# ROAR: Unifying Runs across Heterogeneous AI-Driven Research Systems

> 全文为英语

**Published:** 2026年10月6日
**Author:** Leo Y. Lin, Vishakha Ramani, Z. Berkay Celik, Paul Castro, Marquita Ellis
**Source:** arXiv — cs.AI
**Language:** en-US
**HTML:** https://aiqazaqstan.com/zh/articles/roar-unifying-runs-across-heterogeneous-ai-driven-research-systems

Each run of an AI-driven research system (ADRS) is an expensive search over a vast solution space, and dependable evaluation requires many runs, making run data both costly to produce and valuable to retain for large-scale analysis. Yet this data remains fragmented: teams…

> 内容来自原始来源： **arXiv — cs.AI**
> [在 arXiv — cs.AI 阅读全文](https://arxiv.org/abs/2610.03966)

**标签：** #arXiv

---

*AI Qazaqstan — non-commercial informational portal about AI in Kazakhstan. Machine translations and summaries are AI-generated.*