SOURCE-LINKED INTELLIGENCE
Memory Compression for High-Fanout Agent Sandboxes
High-fanout agent workloads create a growing memory bottleneck because a single task may spawn many concurrent sandbox sessions. Yet these sandboxes are far from independent: they originate from a shared template and execute related trajectories, exposing substantial template-relative and cross-sandbox memory redundancy. Conventional memory compression is poorly matched to this setting in three fundamental dimensions: how to compress, because they fail to exploit similarity across non-identical sandbox pages; what to compress, because they control page-fault overhead through conservative page
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-10T09:25:43.000Z
First collected: 2026-09-20T19:02:05.452Z. This is not the publication date.