PatchKV: Efficient KV Cache Recovery for Dynamically Edited LLM Contexts
Long-running LLM agent workflows often revise interior context spans while retaining long suffixes. Although suffix tokens remain unchanged, altered causal histories and rotary positions prevent exact reuse of their offloaded key-value (KV) states. Full suffix recomputation wastes prefill work, while indiscriminate reuse propagates stale states and full-precision restoration adds data movement. We present PatchKV, a profile-guided recovery system for suffix-preserving revisions. PatchKV decomposes adjacent context versions into an exact prefix, an updated span, and an aligned suffix. It predicts an edit-local dirty region using an offline length-conditioned drift model, augments this regi...
| Authors | Guotao Yang, Rui Guo, Siwei He et al. |
|---|---|
| Primary category | cs.DC |
| Published | 18 August 2026 |
| Last updated at source | 18 August 2026 |
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