ValueDiff: Value-Geometric KV Cache Eviction for Sink-Suppressed LLMs
Modern LLMs with QK-normalization, gated attention, learned attention sinks, or logit softcapping exhibit weaker persistent attention sinks, on which existing KV cache eviction methods primarily rely. We observe that across these models, weaker sinks co-occur with greater value-vector dispersion relative to key-vector dispersion. Motivated by this value-side dispersion, we present ValueDiff, a value-geometric eviction that ranks tokens by the L2 deviation of their value vectors from the cache mean. The same score arises as the minimal-disturbance eviction under a max-entropy assumption about future attention. We evaluate under fixed cache budgets, with eviction at every block boundary dur...
| Authors | Junyoung Park, Jungwook Choi, Mingu Lee |
|---|---|
| Primary category | cs.LG |
| Published | 20 September 2026 |
| Last updated at source | 6 October 2026 |
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