AlignPred: Error-Controlled KV Cache Compression via Alignment and Predictive Coding
Long-running agents retain KV caches across turns and sessions for hours or days. Compressing these persistent caches requires reducing storage while controlling reconstruction error. We present AlignPred, a codec that combines local alignment with predictive coding under a configurable KV reconstruction-error budget. Local orthogonal transforms align related heads or layers into a common coordinate frame, allowing AlignPred to combine token-wise prediction with same-token prediction across heads or layers. Residuals are quantized on an error-bounded lattice and entropy-coded, without learned predictors, encoder-side mode search, or large joint transforms. Across three attention mechanism...
| Authors | Xu Yang, Jiapeng Zhang, Zhiwei Zuo et al. |
|---|---|
| Primary category | cs.PF |
| Published | 13 October 2026 |
| Last updated at source | 13 October 2026 |
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