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This study addresses the catastrophic forgetting problem that occurs when sequentially learning successive tasks using Low-Rank Adaptation (LoRA) from a lifelong learning perspective and proposes Subspace Protection with Allocated Capacity for Efficient Continual Adaptation (SPACE-LoRA).
The results show that learning when and how strongly to update each sample supports stable and efficient post-deployment stream adaptation while avoiding unnecessary updates.
This letter proposes cross-IP request coalescing, which relocates the fan-out point from the guest to the SPDK vhost-user backend, and achieves up to 1.78x lower latency than the per-device baseline, with the benefit growing as concurrency increases.
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