3 citations · 5 across the 9 of their papers we have counts for
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cs.LG2023★ 3 cited
mLoRA: Fine-Tuning LoRA Adapters via Highly-Efficient Pipeline Parallelism in Multiple GPUs
Zhengmao Ye, Dengchun Li, Zetao Hu +8
Transformer-based, pre-trained large language models (LLMs) have demonstrated outstanding performance across diverse domains, particularly in the emerging {\em pretrain-then-finetu…
cs.DC2023
DLRover-RM: Resource Optimization for Deep Recommendation Models Training in the Cloud
Qinlong Wang, Tingfeng Lan, Yinghao Tang +8
Deep learning recommendation models (DLRM) rely on large embedding tables to manage categorical sparse features. Expanding such embedding tables can significantly enhance model per…