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Paper · arXiv

ATTUNER: Recomputation-Free KV Cache Reuse via Query-Side Adaptation

Large language model (LLM) agents repeatedly load reusable content, such as skills, documents, and memory entries, into the current context. Re-encoding this content for every request wastes computation. Position-independent caching (PIC) alleviates this by encoding each artifact independently and reusing its key-value (KV) states at arbitrary positions, but it incurs a quality loss relative to full-context prefill. Existing methods repair this loss by restoring global position IDs or recomputing selected tokens. In this work, we isolate the source of the loss, finding that the positional mismatch has minor effect, and independently cached artifacts retain faithful representations: readin...

AuthorsXinghao Chen, Junnan Dong, Cai Ke et al.
Primary categorycs.CL
Published29 September 2026
Last updated at source29 September 2026
cs.CL
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