Every Cache Entry Earns Its Place: Global Allocation of Resolution and Coverage for KV Cache Compression
As large language models (LLMs) process increasingly long contexts, KV cache storage and repeated access have become a major bottleneck. Existing KV cache compression methods rely on predefined, fixed compression rules and are typically developed around either token eviction or merging. As a result, cache resources can neither flow freely across layers, heads, and context slots, nor be jointly allocated to balance local resolution and information coverage. Therefore, we propose GraceKV, a global approach for the allocation of resolution and coverage in KV cache compression, and formulate the compression process as a global resource allocation problem under a fixed cache budget. GraceKV tr...
| Authors | Haolin Tian, Yuzhe Liu, Tonghan Wang |
|---|---|
| Primary category | cs.LG |
| Published | 7 August 2026 |
| Last updated at source | 10 October 2026 |
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