RouteSparse: Input-Conditional Pattern Routing for Budgeted Long-Context Prefilling
Dynamic sparse attention can reduce the quadratic cost of long-context prefilling without changing model weights. MInference assigns each attention head one pattern offline and estimates that pattern's sparse indices for every prompt. This design is efficient, but it assumes that a head's preferred pattern and sparsity budget remain suitable across inputs. We introduce RouteSparse, which routes each head and prompt segment among a small library of GPU-efficient sparse patterns. A low-cost probe estimates pattern utility and uncertainty; a latency-aware router then selects a pattern and budget, while uncertain cases fall back to a denser mask. We formulate routing as constrained risk minim...
| Authors | Chao Zhang, Yifan Ji, Ziyan Zhang et al. |
|---|---|
| Primary category | cs.CL |
| Published | 29 August 2026 |
| Last updated at source | 29 August 2026 |
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