42 citations · 49 across the 5 of their papers we have counts for
3 papers
cs.LG2023
BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs
Zhen Yang, Tinglin Huang, Ming Ding +5
In-Batch contrastive learning is a state-of-the-art self-supervised method that brings semantically-similar instances close while pushing dissimilar instances apart within a mini-b…
cs.LG2023★ 6 cited
GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner
Zhenyu Hou, Yufei He, Yukuo Cen +4
Graph self-supervised learning (SSL), including contrastive and generative approaches, offers great potential to address the fundamental challenge of label scarcity in real-world g…
cs.LG2022★ 42 cited
Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries
Xiao Liu, Shiyu Zhao, Kai Su +6
Knowledge graph (KG) embeddings have been a mainstream approach for reasoning over incomplete KGs. However, limited by their inherently shallow and static architectures, they can h…