Changhua Meng

According to our database, Changhua Meng authored at least 32 papers between 2021 and 2024.

Collaborative distances:

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

2024

E-ANT: A Large-Scale Dataset for Efficient Automatic GUI NavigaTion.

Ke Wang, Tianyu Xia, Zhangxuan Gu, Yi Zhao, Shuheng Shen, Changhua Meng, Weiqiang Wang, Ke Xu

CoRR, 2024

TroubleLLM: Align to Red Team Expert.

Zhuoer Xu, Jianping Zhang, Shiwen Cui, Changhua Meng, Weiqiang Wang

CoRR, 2024

GraphRPM: Risk Pattern Mining on Industrial Large Attributed Graphs.

Sheng Tian, Xintan Zeng, Yifei Hu, Baokun Wang, Yongchao Liu, Yue Jin, Changhua Meng, Chuntao Hong, Tianyi Zhang, Weiqiang Wang

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2024

PC²: Pseudo-Classification Based Pseudo-Captioning for Noisy Correspondence Learning in Cross-Modal Retrieval.

Yue Duan, Zhangxuan Gu, Zhenzhe Ying, Lei Qi, Changhua Meng, Yinghuan Shi

Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective.

Yunfei Liu, Jintang Li, Yuehe Chen, Ruofan Wu, Ericbk Wang, Jing Zhou, Sheng Tian, Shuheng Shen, Xing Fu, Changhua Meng, Weiqiang Wang, Liang Chen

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks.

Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Baokun Wang, Changhua Meng, Zibin Zheng, Liang Chen

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Mirror-Consistency: Harnessing Inconsistency in Majority Voting.

Siyuan Huang, Zhiyuan Ma, Jintao Du, Changhua Meng, Weiqiang Wang, Zhouhan Lin

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Enhancing Distantly Supervised Named Entity Recognition with Strong Label Guided Lottery Training.

Zhiyuan Ma, Jintao Du, Changhua Meng, Weiqiang Wang

Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

Adversarial Robust Safeguard for Evading Deep Facial Manipulation.

Jiazhi Guan, Yi Zhao, Zhuoer Xu, Changhua Meng, Ke Xu, Youjian Zhao

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

2023

LasTGL: An Industrial Framework for Large-Scale Temporal Graph Learning.

Jintang Li, Jiawang Dan, Ruofan Wu, Jing Zhou, Sheng Tian, Yunfei Liu, Baokun Wang, Changhua Meng, Weiqiang Wang, Yuchang Zhu, Liang Chen, Zibin Zheng

CoRR, 2023

Hetero$^2$Net: Heterophily-aware Representation Learning on Heterogenerous Graphs.

Jintang Li, Zheng Wei, Jiawang Dan, Jing Zhou, Yuchang Zhu, Ruofan Wu, Baokun Wang, Zhang Zhen, Changhua Meng, Hong Jin, Zibin Zheng, Liang Chen

CoRR, 2023

Self-supervision meets kernel graph neural models: From architecture to augmentations.

Jiawang Dan, Ruofan Wu, Yunpeng Liu, Baokun Wang, Changhua Meng, Tengfei Liu, Tianyi Zhang, Ningtao Wang, Xing Fu, Qi Li, Weiqiang Wang

CoRR, 2023

On the Robustness of Latent Diffusion Models.

Jianping Zhang, Zhuoer Xu, Shiwen Cui, Changhua Meng, Weibin Wu, Michael R. Lyu

CoRR, 2023

Less Can Be More: Unsupervised Graph Pruning for Large-scale Dynamic Graphs.

Jintang Li, Sheng Tian, Ruofan Wu, Liang Zhu, Wenlong Zhao, Changhua Meng, Liang Chen, Zibin Zheng, Hongzhi Yin

CoRR, 2023

DEDGAT: Dual Embedding of Directed Graph Attention Networks for Detecting Financial Risk.

Jiafu Wu, Mufeng Yao, Dong Wu, Mingmin Chi, Baokun Wang, Ruofan Wu, Xin Fu, Changhua Meng, Weiqiang Wang

CoRR, 2023

DiffUTE: Universal Text Editing Diffusion Model.

Haoxing Chen, Zhuoer Xu, Zhangxuan Gu, Jun Lan, Xing Zheng, Yaohui Li, Changhua Meng, Huijia Zhu, Weiqiang Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Hierarchical Dynamic Image Harmonization.

Haoxing Chen, Zhangxuan Gu, Yaohui Li, Jun Lan, Changhua Meng, Weiqiang Wang, Huaxiong Li

Proceedings of the 31st ACM International Conference on Multimedia, 2023

What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders.

Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs.

Sheng Tian, Jihai Dong, Jintang Li, Wenlong Zhao, Xiaolong Xu, Baokun Wang, Bowen Song, Changhua Meng, Tianyi Zhang, Liang Chen

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Self-supervision meets kernel graph neural models: From architecture to augmentations.

Jiawang Dan, Ruofan Wu, Yunpeng Liu, Baokun Wang, Changhua Meng, Tengfei Liu, Tianyi Zhang, Ningtao Wang, Xing Fu, Qi Li, Weiqiang Wang

Proceedings of the IEEE International Conference on Data Mining, 2023

Backpropagation Path Search On Adversarial Transferability.

Zhuoer Xu, Zhangxuan Gu, Jianping Zhang, Shiwen Cui, Changhua Meng, Weiqiang Wang

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Mobile User Interface Element Detection Via Adaptively Prompt Tuning.

Zhangxuan Gu, Zhuoer Xu, Haoxing Chen, Jun Lan, Changhua Meng, Weiqiang Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

GUARD: Graph Universal Adversarial Defense.

Jintang Li, Jie Liao, Ruofan Wu, Liang Chen, Zibin Zheng, Jiawang Dan, Changhua Meng, Weiqiang Wang

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

Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks.

Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Towards Learning to Discover Money Laundering Sub-network in Massive Transaction Network.

Ziwei Chai, Yang Yang, Jiawang Dan, Sheng Tian, Changhua Meng, Weiqiang Wang, Yifei Sun

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

DiffusionInst: Diffusion Model for Instance Segmentation.

Zhangxuan Gu, Haoxing Chen, Zhuoer Xu, Jun Lan, Changhua Meng, Weiqiang Wang

CoRR, 2022

MaskGAE: Masked Graph Modeling Meets Graph Autoencoders.

Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang

CoRR, 2022

GUARD: Graph Universal Adversarial Defense.

Jintang Li, Jie Liao, Ruofan Wu, Liang Chen, Changhua Meng, Zibin Zheng, Weiqiang Wang

CoRR, 2022

MT-GBM: A Multi-Task Gradient Boosting Machine with Shared Decision Trees.

Zhenzhe Ying, Zhuoer Xu, Zhifeng Li, Weiqiang Wang, Changhua Meng

CoRR, 2022

A2: Efficient Automated Attacker for Boosting Adversarial Training.

Zhuoer Xu, Guanghui Zhu, Changhua Meng, Shiwen Cui, Zhenzhe Ying, Weiqiang Wang, Ming Gu, Yihua Huang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

XYLayoutLM: Towards Layout-Aware Multimodal Networks For Visually-Rich Document Understanding.

Zhangxuan Gu, Changhua Meng, Ke Wang, Jun Lan, Weiqiang Wang, Ming Gu, Liqing Zhang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

A Vertical Federated Learning Framework for Graph Convolutional Network.

Xiang Ni, Xiaolong Xu, Lingjuan Lyu, Changhua Meng, Weiqiang Wang

CoRR, 2021