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arXiv AI By Ryan Lum, Yongfeng Zhang

Kernel-Managed Shared Memory for System-Wide Personalization

Read the original on arXiv AI →

The paper introduces kernel‑managed shared memory, a system‑level abstraction that lets specialized agents write structured, tagged memories while the agent‑system kernel controls retrieval, privacy, and prompt injection. Implemented on AIOS, this design outperforms unmanaged external memory, standard retrieval‑augmented injection, and full context concatenation across GPT‑4o, Llama‑3.1:8B, and Qwen‑2.5:7B, improving personalization scores by 2.4‑4.0 points on a 5‑point scale and reducing latency and token usage by 15‑61%. The results show that centralizing memory management in the kernel delivers most personalization benefits at a fraction of the cost.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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