1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.DC2025
MegaScale-Data: Scaling Dataloader for Multisource Large Foundation Model Training
Juntao Zhao, Qi Lu, Wei Jia +13
Modern frameworks for training large foundation models (LFMs) employ dataloaders in a data-parallel manner, with each loader processing a disjoint subset of training data. When pre…
cs.LG2024★ 1 cited
Model Balancing Helps Low-data Training and Fine-tuning
Zihang Liu, Yuanzhe Hu, Tianyu Pang +3
Recent advances in foundation models have emphasized the need to align pre-trained models with specialized domains using small, curated datasets. Studies on these foundation models…