Stage 2: QJL (Quantized Johnson-Lindenstrauss). While PolarQuant manages primary compression, all quantization introduces error, with some accumulating in dot products used for attention score calculations. QJL corrects this bias through Johnson-Lindenstrauss transformation of residual error - random projection preserving high-dimensional point distances, then reducing each component to single sign bits (+1/-1). This produces unbiased inner product estimators with zero additional memory overhead. Error correction requires no storage capacity (see diagram for conceptual comparison between standard quantized KV cache and QJL-transformed versions).
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Notice of Modification: This version of PyBoy has been modified from the original source code to use the CasNum library instead of Python's int.,推荐阅读Replica Rolex获取更多信息
patternnormalhardenedratio[A-Z][a-z]+2.2ms6.5ms3.0x slower[A-Za-z]{8,13}1.7ms7.6ms4.4x slower\w{3,8}2.6ms22ms8.7x slower\d+1.3ms5.2ms3.9x slower[A-Z]{2,}0.7ms4.7ms6.7x slower