turboquant-py implements the TurboQuant and QJL vector quantization algorithms from Google Research (ICLR 2026 / AISTATS 2026). It compresses high-dimensional floating-point vectors to 1-4 bits per ...
Vector Post-Training Quantization (VPTQ) is a novel Post-Training Quantization method that leverages Vector Quantization to high accuracy on LLMs at an extremely low bit-width (<2-bit). VPTQ can ...
Do you remember the early days of social media? The promise of connection, of democratic empowerment, of barriers crumbling and gates opening? In those heady days, the co-founder of Twitter said that ...
All of these numbers are used by the algorithm to compute a "Power Index" number for each driver. The higher the Power Index number, the faster that driver is expected to be during the race. All of ...
ABSTRACT: This paper proposes a voice codification based on two algorithms that make the wave form codification in time domain. The first uses the significant impulse model (SIM), which has as a goal ...
Abstract: The vector quantization was a powerful technique in image compression. The widely used method such as the Linde-Buzo-Gray (LBG) algorithm always generated local optimal codebook. Recently, ...
Abstract: An improved LBG algorithm for vector quantization is introduced in this paper. Its basic idea is classifying the input vectors based on space partition with a variational distance threshold.
ABSTRACT: In this paper, we present a theoretical codebook design method for VQ-based fast face recognition algorithm to im-prove recognition accuracy. Based on the systematic analysis and ...
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