11 citations · 11 across the 2 of their papers we have counts for
2 papers
cs.CV2024★ 11 cited
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Brandon McKinzie, Zhe Gan, Jean-Philippe Fauconnier +29
In this work, we discuss building performant Multimodal Large Language Models (MLLMs). In particular, we study the importance of various architecture components and data choices. T…
eess.IV2024
Progressive Divide-and-Conquer via Subsampling Decomposition for Accelerated MRI
Chong Wang, Lanqing Guo, Yufei Wang +3
Deep unfolding networks (DUN) have emerged as a popular iterative framework for accelerated magnetic resonance imaging (MRI) reconstruction. However, conventional DUN aims to recon…