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News/SelKV: Selective KV Cache Merging with Per-Token Merge-or-Drop and Attention Compensation
arxiv
PublishedJuly 21, 2026 at 4:00 AM
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SelKV: Selective KV Cache Merging with Per-Token Merge-or-Drop and Attention Compensation

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arXiv:2607.16213v1 Announce Type: new Abstract: Large Language Models (LLMs) generate text autoregressively, relying on a key-value (KV) cache whose memory footprint grows linearly with context length, creating a major bottleneck. Recent compression methods mitigate this cost via token merging; howe

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