GitHub

SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference

In vision-language models (VLMs), visual tokens usually consume a significant amount of computational overhead, despite their sparser information density compared to text tokens. To address this, ...
IEEE

Matrix-Inversion-Free Sparse Bayesian Learning for High-Resolution Radar Imagery via Improved Variational Inference

Abstract: Sparse Bayesian learning (SBL) is an advanced statistical framework that dominantly enhances the sparse features of targets of interest in radar imagery. A widely adopted strategy for ...
GitHub

ryp: R inside Python

running R code inside Python quickly transferring huge datasets between Python (NumPy/pandas/polars) and R without writing to disk interactively working in both languages at the same time ...
IEEE

Toward Greener Matrix Operations by Lossless Compressed Formats

Abstract: Sparse matrix-vector multiplication (SpMV) is a fundamental operation in machine learning, scientific computing, and graph algorithms. In this paper, we investigate the space, time, and ...