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cs.LG2026
RateQuant: Optimal Mixed-Precision KV Cache Quantization via Rate-Distortion Theory
Fei Zuo, Zikang Zhou, Hao Cong +2
Large language models cache all previously computed key-value (KV) pairs during generation, and this KV cache grows linearly with sequence length, making it a primary memory bottle…
cs.LG2026
FairyFuse: Multiplication-Free LLM Inference on CPUs via Fused Ternary Kernels
Fei Zuo, Xiaoyan Xi, Quanyi Zeng +2
Large language models are increasingly deployed on CPU-only platforms where memory bandwidth is the primary bottleneck for autoregressive generation. Weight quantization to four bi…