6 citations · 7 across the 2 of their papers we have counts for
2 papers
cs.DC2023★ 1 cited
SPT: Fine-Tuning Transformer-based Language Models Efficiently with Sparsification
Yuntao Gui, Xiao Yan, Peiqi Yin +2
Transformer-based large language models (e.g., BERT and GPT) achieve great success, and fine-tuning, which tunes a pre-trained model on a task-specific dataset, is the standard pra…
cs.LG2021★ 6 cited
Calibrating and Improving Graph Contrastive Learning
Kaili Ma, Haochen Yang, Han Yang +2
Graph contrastive learning algorithms have demonstrated remarkable success in various applications such as node classification, link prediction, and graph clustering. However, in u…