iS-KV: Online Low-Rank KV Cache Compression via Block-Incremental SVD
Long chain-of-thought reasoning substantially increases KV-cache memory during autoregressive decoding, as every generated token introduces new key and value states and causes the cache to grow linearly with decoding length. Existing KV-cache compression methods typically control this growth through token eviction, but irreversible deletion can remove historical states that later reasoning may need to revisit. SVD-based low-rank compression provides an alternative by retaining all positions with a more compact representation. However, extending it from a fixed prompt cache to online decoding is non-trivial. Through our investigation, we find that if the basis is updated for new tokens whi...
| Authors | Yiren Zhao, Guanghui Song, Tianrui Qin et al. |
|---|---|
| Primary category | cs.AI |
| Published | 2 October 2026 |
| Last updated at source | 2 October 2026 |
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