In industrial recommendation systems, the shift toward Generative Retrieval (GR) is replacing traditional embedding-based nearest neighbor search with Large Language Models (LLMs). These models ...
School of Physical Science and Technology & Collaborative Innovation Center of Suzhou Nano Science and Technology, Soochow University, Suzhou 215006, China Suzhou Key Laboratory of Intelligent ...
ABSTRACT: Node renumbering is an important step in the solution of sparse systems of equations. It aims to reduce the bandwidth and profile of the matrix. This allows for the speeding up of the ...
ABSTRACT: Properties from random matrix theory allow us to uncover naturally embedded signals from different data sets. While there are many parameters that can be changed, including the probability ...
MICSI-RMT is a significant breakthrough as the first market solution designed to enhance the signal-to-noise ratio (SNR) for diffusion and functional MRI. Diffusion MRI involves the exponential signal ...
Presenting an algorithm that solves linear systems with sparse coefficient matrices asymptotically faster than matrix multiplication for any ω > 2. Our algorithm can be viewed as an efficient, ...
Is your feature request related to a problem? Please describe. I am not sure if I am doing something wrong but I am using scipy.sparse.csr_matrix object and contract it with a np.ndarray object using ...
Cross-encoder (CE) models evaluate similarity by simultaneously encoding a query-item pair, outperforming the dot-product with embedding-based models at estimating query-item relevance. Current ...
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