Ming Gu

According to our database, Ming Gu authored at least 14 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Towards Scalable Web Accessibility Audit with MLLMs as Copilots.

Ming Gu, Ziwei Wang, Sicen Lai, Zirui Gao, Sheng Zhong, Jiajun Bu

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Towards Scalable Web Accessibility Audit with MLLMs as Copilots.

Ming Gu, Ziwei Wang, Sicen Lai, Zirui Gao, Sheng Zhou, Jiajun Bu

CoRR, November, 2025

AWA.

Ming Gu, Sheng Zhou, Jiajun Bu

Dataset, November, 2025

NOS-raw.

Ming Gu, Sheng Zhou, Jiajun Bu

Dataset, February, 2025

NOS.

Ming Gu, Sheng Zhou, Jiajun Bu

Dataset, February, 2025

Heterophilous distribution propagation for Graph Neural Networks.

Zhuonan Zheng, Sheng Zhou, Hongjia Xu, Ming Gu, Yilun Xu, Ao Li, Yuhong Li, Jingjun Gu, Jiajun Bu

Neural Networks, 2025

Frequency Self-Adaptation Graph Neural Network for Unsupervised Graph Anomaly Detection.

Ming Gu, Gaoming Yang, Zhuonan Zheng, Meihan Liu, Haishuai Wang, Jiawei Chen, Sheng Zhou, Jiajun Bu

Neural Networks, 2025

Towards an Inclusive Mobile Web: A Dataset and Framework for Focusability in UI Accessibility.

Ming Gu, Lei Pei, Sheng Zhou, Ming Shen, Yuxuan Wu, Zirui Gao, Ziwei Wang, Shuo Shan, Wei Jiang, Yong Li, Jiajun Bu

Proceedings of the ACM on Web Conference 2025, 2025

Towards a Unified Framework of Clustering-based Anomaly Detection.

Zeyu Fang, Ming Gu, Sheng Zhou, Jiawei Chen, Qiaoyu Tan, Haishuai Wang, Jiajun Bu

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Structure enhanced prototypical alignment for unsupervised cross-domain node classification.

Meihan Liu, Zhen Zhang, Ning Ma, Ming Gu, Haishuai Wang, Sheng Zhou, Jiajun Bu

Neural Networks, 2024

Universal Inceptive GNNs by Eliminating the Smoothness-generalization Dilemma.

Ming Gu, Zhuonan Zheng, Sheng Zhou, Meihan Liu, Jiawei Chen, Tanyu Qiao, Liangcheng Li, Jiajun Bu

CoRR, 2024

Revisiting the Message Passing in Heterophilous Graph Neural Networks.

Zhuonan Zheng, Yuanchen Bei, Sheng Zhou, Yao Ma, Ming Gu, Hongjia Xu, Chengyu Lai, Jiawei Chen, Jiajun Bu

CoRR, 2024

Rethinking Propagation for Unsupervised Graph Domain Adaptation.

Meihan Liu, Zeyu Fang, Zhen Zhang, Ming Gu, Sheng Zhou, Xin Wang, Jiajun Bu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Homophily-enhanced Structure Learning for Graph Clustering.

Ming Gu, Gaoming Yang, Sheng Zhou, Ning Ma, Jiawei Chen, Qiaoyu Tan, Meihan Liu, Jiajun Bu

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023