132 citations · 141 across the 3 of their papers we have counts for
3 papers
cs.LG2021
First Place Solution of KDD Cup 2021 & OGB Large-Scale Challenge Graph Prediction Track
Chengxuan Ying, Mingqi Yang, Shuxin Zheng +7
In this technical report, we present our solution of KDD Cup 2021 OGB Large-Scale Challenge - PCQM4M-LSC Track. We adopt Graphormer and ExpC as our basic models. We train each mode…
cs.LG2021★ 132 cited
Do Transformers Really Perform Bad for Graph Representation?
Chengxuan Ying, Tianle Cai, Shengjie Luo +5
The Transformer architecture has become a dominant choice in many domains, such as natural language processing and computer vision. Yet, it has not achieved competitive performance…
cs.CL2021★ 9 cited
LazyFormer: Self Attention with Lazy Update
Chengxuan Ying, Guolin Ke, Di He +1
Improving the efficiency of Transformer-based language pre-training is an important task in NLP, especially for the self-attention module, which is computationally expensive. In th…