11 citations · 11 across the 3 of their papers we have counts for
3 papers
cs.LG2025
AXLearn: Modular, Hardware-Agnostic Large Model Training
Mark Lee, Chang Lan, Tom Gunter +34
AXLearn is a production system which facilitates scalable and high-performance training of large deep learning models. Compared to other state-of-art deep learning systems, AXLearn…
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…
cs.CL2023
Learning to Skip for Language Modeling
Dewen Zeng, Nan Du, Tao Wang +4
Overparameterized large-scale language models have impressive generalization performance of in-context few-shot learning. However, most language models allocate the same amount of…