KVBoost enables chunk-level key-value cache reuse with deviation-guided recomputation for efficient large language model inference; reduces prefill latency in HuggingFace-compatible decoders.
Read the original at arxiv.org→arXiv:2608.21362v1 Announce Type: new Abstract: Transformer-based large language models (LLMs) incur high prefill latency because key-value (KV) tensors must be recomputed for each request. Existing prefix-caching...
Original headline: "KVBoost: Chunk-Level Key-Value Cache Reuse with Deviation-Guided Recomputation for Efficient Large Language Model Inference"
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- Aug 25, 04:00 UTC arXiv cs.AI lead source KVBoost: Chunk-Level Key-Value Cache Reuse with Deviation-Guided Recomputation for Efficient Large Language Model Inference