arXiv:2605. 19035v2 Announce Type: replace Abstract: The rapid advancement of Large Language Models has given rise to autonomous LLM-based agents capable of complex reasoning and execution.
By Yixiang Yao, Yuhang Yao, Xinyi Fan, Jiechao Gao, Jie Wang, Minjia Zhang, Srivatsan Ravi, Carlee Joe-Wong
arXiv:2607. 02186v1 Announce Type: new Abstract: Software development is a complex task that demands cooperation among agents with diverse roles.
By Temitayo Olamilekan Ogunsusi, Lijun Qian, Xishuang Dong
Incident‑Arena is a new benchmark for AI coding agents focused on production incident response, featuring 20 tasks derived from real‑world open‑source software. Each task deploys a production application on an ephemerally created Kubernetes cluster, injects faults at various layers, and applies a sustained load profile. The benchmark introduces functional verifiers that maintain system‑level metrics while ensuring safe repairs, and shows that current frontier models achieve below 64.3% across the tasks, highlighting challenges in diagnosis, repair, and regression safety.
By Andre Fu, Malik Drabla, Leon Liu, Meji Abidoye, Marek Suppa, Lata Mishra, Adnan El Assadi, Yiyuan Li
arXiv:2606. 09122v1 Announce Type: cross Abstract: Cloud network infrastructure at hyperscale presents unique operational challenges where traditional human-driven incident response cannot keep pace with the volume, velocity, and complexity of failures.
By Arun Malik
As Large Language Models (LLMs) evolve into autonomous agents, the need for unified evaluation infrastructure becomes critical. However, current evaluation pipelines remain highly fragmented and tightly coupled, hindering reproducibility and causing redundant engineering.
arXiv:2605. 07161v3 Announce Type: replace Abstract: AI agents are increasingly used to diagnose and mitigate failures in production systems, known as agentic Site Reliability Engineering (SRE).
By Jackson Clark, Yiming Su, Saad Mohammad Rafid Pial, Yifang Tian, Lily Gniedziejko, Hans-Arno Jacobsen, Yinfang Chen, Tianyin Xu