most citedTowards Data-centric Graph Machine Learning: Review and Outlook

9 citations · 22 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2024

Online GNN Evaluation Under Test-time Graph Distribution Shifts

Xin Zheng, Dongjin Song, Qingsong Wen +2

Evaluating the performance of a well-trained GNN model on real-world graphs is a pivotal step for reliable GNN online deployment and serving. Due to a lack of test node labels and…

cs.LG20243 cited

Graph Learning under Distribution Shifts: A Comprehensive Survey on Domain Adaptation, Out-of-distribution, and Continual Learning

Man Wu, Xin Zheng, Qin Zhang +4

Graph learning plays a pivotal role and has gained significant attention in various application scenarios, from social network analysis to recommendation systems, for its effective…

cs.LG20238 cited

GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels

Xin Zheng, Miao Zhang, Chunyang Chen +3

Evaluating the performance of graph neural networks (GNNs) is an essential task for practical GNN model deployment and serving, as deployed GNNs face significant performance uncert…

cs.LG20239 cited

Towards Data-centric Graph Machine Learning: Review and Outlook

Xin Zheng, Yixin Liu, Zhifeng Bao +4

Data-centric AI, with its primary focus on the collection, management, and utilization of data to drive AI models and applications, has attracted increasing attention in recent yea…

cs.CL2023

Toward Unified Controllable Text Generation via Regular Expression Instruction

Xin Zheng, Hongyu Lin, Xianpei Han +1

Controllable text generation is a fundamental aspect of natural language generation, with numerous methods proposed for different constraint types. However, these approaches often…

cs.CL2023

DialogVCS: Robust Natural Language Understanding in Dialogue System Upgrade

Zefan Cai, Xin Zheng, Tianyu Liu +7

In the constant updates of the product dialogue systems, we need to retrain the natural language understanding (NLU) model as new data from the real users would be merged into the…