Papers with Paged Attention

1 papers
EQUIP: EQUivariant preserving In-Place updates for Efficient Token Pruning (2026.acl-long)

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Challenge: Token-pruning methods cause "holes" in KV tensors, posing major challenges . equip reduces recomputation of rotation operations through in-place update, caching and re-indexing .
Approach: They propose an EQUIP-based in-place token update mechanism that preserves the equivariance property of the operations performed in the attention computation.
Outcome: EQUIP reduces recomputation of rotation operations and reduces eviction overheads . it achieves geomean speedups of 1.62 (or 1.47) over StreamingLLM and 3.45 ( or 1.86)

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