Orca-Bench: How Ready Are Language Model Agents for Oncall?
Computer Science > Computation and Language arXiv:2607.28545 (cs) [Submitted on 30 Jul 2026] Title:ORCA-bench: How Ready Are Language Model Agents for Oncall? We introduce ORCA-bench, a benchmark that puts general-purpose coding agents in a production-fidelity oncall setting. Ground-truth symptoms are curated and signed off by expert SREs, and our LLM-as-judge is independently re-scored by humans (Cohen's $\kappa_w=0.90$).
- ▪Computer Science > Computation and Language arXiv:2607.28545 (cs) [Submitted on 30 Jul 2026] Title:ORCA-bench: How Ready Are Language Model Agents for Oncall?
- ▪We introduce ORCA-bench, a benchmark that puts general-purpose coding agents in a production-fidelity oncall setting.
- ▪Ground-truth symptoms are curated and signed off by expert SREs, and our LLM-as-judge is independently re-scored by humans (Cohen's $\kappa_w=0.90$).
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| Original publisher | arXiv.org |
| Canonical URL | https://arxiv.org/abs/2607.28545 |
| Publication time | Fri, 31 Jul 2026 18:32:43 +0000 |
| Retrieval time | 2026-07-31T19:14:02.657Z |
| Last seen | 2026-07-31T19:14:02.657Z |
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Computer Science > Computation and Language arXiv:2607.28545 (cs) [Submitted on 30 Jul 2026] Title:ORCA-bench: How Ready Are Language Model Agents for Oncall? Authors:Albert Gong, Kyuseong Choi, Abhineet Agarwal, Jason Schechner, Ryan Huang, Raj Agrawal, Anish Agarwal, Raaz Dwivedi View a PDF of the paper titled ORCA-bench: How Ready Are Language Model Agents for Oncall?, by Albert Gong and 7 other authors View PDF HTML (experimental) Abstract:Large language models can write, patch, and search code, but oncall root cause analysis (RCA) demands something different: reasoning over noisy metrics, logs, traces, and source code, starting from ambiguous user-facing reports, often hours after the incident began.
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