HACK performs attention matrix multiplications directly on 2-bit quantized key-value cache entries, eliminating per-iteration dequantization and cutting end-to-end latency in disaggregated LLM serving.
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HACK: Homomorphic Acceleration via Compression of the Key-Value Cache for Disaggregated LLM Inference
HACK performs attention matrix multiplications directly on 2-bit quantized key-value cache entries, eliminating per-iteration dequantization and cutting end-to-end latency in disaggregated LLM serving.