most citedTCL: Transformer-based Dynamic Graph Modelling via Contrastive Learning

24 citations · 29 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2022★ 2 cited

Knowledge Distillation of Transformer-based Language Models Revisited

Chengqiang Lu, Jianwei Zhang, Yunfei Chu +5

In the past few years, transformer-based pre-trained language models have achieved astounding success in both industry and academia. However, the large model size and high run-time…

cs.LG2021★ 1 cited

Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI

Jiangchao Yao, Shengyu Zhang, Yang Yao +15

Influenced by the great success of deep learning via cloud computing and the rapid development of edge chips, research in artificial intelligence (AI) has shifted to both of the co…

cs.IR2021★ 2 cited

Dynamic Sequential Graph Learning for Click-Through Rate Prediction

Yunfei Chu, Xiaofu Chang, Kunyang Jia +2

Click-through rate prediction plays an important role in the field of recommender system and many other applications. Existing methods mainly extract user interests from user histo…

cs.LG2021★ 24 cited

TCL: Transformer-based Dynamic Graph Modelling via Contrastive Learning

Lu Wang, Xiaofu Chang, Shuang Li +7

Dynamic graph modeling has recently attracted much attention due to its extensive applications in many real-world scenarios, such as recommendation systems, financial transactions,…

cs.LG2021

Inductive Granger Causal Modeling for Multivariate Time Series

Yunfei Chu, Xiaowei Wang, Jianxin Ma +3

Granger causal modeling is an emerging topic that can uncover Granger causal relationship behind multivariate time series data. In many real-world systems, it is common to encounte…