AI RESEARCH
TurboAngle: Near-Lossless KV Cache Compression via Uniform Angle Quantization
arXiv CS.AI
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ArXi:2603.27467v1 Announce Type: cross We compress KV cache entries by quantizing angles in the Fast Walsh-Hadamard domain, where a random diagonal rotation makes consecutive element pairs approximately uniformly distributed on the unit circle. We extend this angular quantizer with per-layer early-boost, which independently configures K and V codebook sizes at each layer, allocating higher precision to a model-specific subset of critical layers.