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MeshKV, a KV cache fabric that moves blocks as packetized flows over a lightweight NoC, co-designs TaKV affine striping to spread homes and cut hotspot load and co-designs Mare multicast with verified duplicate suppression, and Pad, which converts bisection back-pressure into useful KV transfer.
KVLearn, a learning-based retention framework that makes keep/evict decisions as first-class cost-optimization choices in disaggregated LLM serving is presented and evaluated on both text and multimodal workloads.
This work introduces RUBRIC, a generator-agnostic filtering framework that formulates synthetic sample selection as a quality-over-quantity optimization problem and shows that RUBRIC improves F1-macro and recall while maintaining comparable ROC-AUC across several generators.
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