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cs.DC2025
R2CC: Reliable and Resilient Collective Communication for Distributed Learning
Wei Wang, Nengneng Yu, Sixian Xiong +1
Modern ML training and inference now span hundreds to tens of thousands of GPUs, where failures can waste 10-15% of GPU hours due to slow recovery. Common network errors and link f…
cs.NI2025
NetArena: Dynamic Benchmarks for AI Agents in Network Automation
Yajie Zhou, Jiajun Ruan, Eric S. Wang +4
As AI agents expand into high-stakes domains like network system operations, evaluating their real-world reliability becomes increasingly critical. However, existing benchmarks ris…