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MoEZip: Routing-Aware KV Cache Compression for Sparse Mixture-of-Experts LLMs

arXiv:2610.30206v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) language models scale model capacity efficiently by activating a small subset of parameters per token. However, in long-context inference, memory remains a major bottleneck because the KV cache grows linearly with sequence len…

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  1. 2026-10-23 04:00 · arXiv cs.LG
    MoEZip: Routing-Aware KV Cache Compression for Sparse Mixture-of-Experts LLMs

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