A Vertical Federated Learning Framework for Graph Convolutional Network. - Xiang Ni; Xiaolong Xu; Lingjuan Lyu; Changhua Meng; Weiqiang Wang 002 (CoRR, 2021)

XYLayoutLM: Towards Layout-Aware Multimodal Networks For Visually-Rich Document Understanding. - Zhangxuan Gu; Changhua Meng; Ke Wang 042; Jun Lan; Weiqiang Wang 002; Ming Gu 011; Liqing Zhang 001 (CVPR, 2022)

A2: Efficient Automated Attacker for Boosting Adversarial Training. - Zhuoer Xu; Guanghui Zhu; Changhua Meng; Shiwen Cui; Zhenzhe Ying; Weiqiang Wang 002; Ming Gu 011; Yihua Huang 001 (NeurIPS, 2022)

MT-GBM: A Multi-Task Gradient Boosting Machine with Shared Decision Trees. - Zhenzhe Ying; Zhuoer Xu; Zhifeng Li; Weiqiang Wang 002; Changhua Meng (CoRR, 2022)

GUARD: Graph Universal Adversarial Defense. - Jintang Li; Jie Liao; Ruofan Wu; Liang Chen 001; Changhua Meng; Zibin Zheng; Weiqiang Wang 002 (CoRR, 2022)

MaskGAE: Masked Graph Modeling Meets Graph Autoencoders. - Jintang Li; Ruofan Wu; Wangbin Sun; Liang Chen 001; Sheng Tian; Liang Zhu; Changhua Meng; Zibin Zheng; Weiqiang Wang 002 (CoRR, 2022)

DiffusionInst: Diffusion Model for Instance Segmentation. - Zhangxuan Gu; Haoxing Chen; Zhuoer Xu; Jun Lan; Changhua Meng; Weiqiang Wang 002 (CoRR, 2022)

Towards Learning to Discover Money Laundering Sub-network in Massive Transaction Network. - Ziwei Chai; Yang Yang 009; Jiawang Dan; Sheng Tian; Changhua Meng; Weiqiang Wang 002; Yifei Sun 002 (AAAI, 2023)

Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks. - Jintang Li; Zhouxin Yu; Zulun Zhu; Liang Chen 001; Qi Yu 001; Zibin Zheng; Sheng Tian; Ruofan Wu; Changhua Meng (AAAI, 2023)

GUARD: Graph Universal Adversarial Defense. - Jintang Li; Jie Liao; Ruofan Wu; Liang Chen 001; Zibin Zheng; Jiawang Dan; Changhua Meng; Weiqiang Wang 002 (CIKM, 2023)

Mobile User Interface Element Detection Via Adaptively Prompt Tuning. - Zhangxuan Gu; Zhuoer Xu; Haoxing Chen; Jun Lan; Changhua Meng; Weiqiang Wang 002 (CVPR, 2023)

Backpropagation Path Search On Adversarial Transferability. - Zhuoer Xu; Zhangxuan Gu; Jianping Zhang 002; Shiwen Cui; Changhua Meng; Weiqiang Wang 002 (ICCV, 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 002; Weiqiang Wang 002 (ICDM (Workshops), 2023)

SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs. - Sheng Tian; Jihai Dong; Jintang Li; Wenlong Zhao 013; Xiaolong Xu; Baokun Wang; Bowen Song; Changhua Meng; Tianyi Zhang; Liang Chen 001 (IJCAI, 2023)

What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders. - Jintang Li; Ruofan Wu; Wangbin Sun; Liang Chen 001; Sheng Tian; Liang Zhu; Changhua Meng; Zibin Zheng; Weiqiang Wang 002 (KDD, 2023)

Hierarchical Dynamic Image Harmonization. - Haoxing Chen; Zhangxuan Gu; Yaohui Li; Jun Lan; Changhua Meng; Weiqiang Wang 002; Huaxiong Li (ACM Multimedia, 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 002 (NeurIPS, 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 002 (CoRR, 2023)

Less Can Be More: Unsupervised Graph Pruning for Large-scale Dynamic Graphs. - Jintang Li; Sheng Tian; Ruofan Wu; Liang Zhu; Wenlong Zhao 013; Changhua Meng; Liang Chen 001; Zibin Zheng; Hongzhi Yin (CoRR, 2023)

On the Robustness of Latent Diffusion Models. - Jianping Zhang 002; Zhuoer Xu; Shiwen Cui; Changhua Meng; Weibin Wu 002; Michael R. Lyu (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 001 (CoRR, 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 002; Yuchang Zhu; Liang Chen 001; Zibin Zheng (CoRR, 2023)

Adversarial Robust Safeguard for Evading Deep Facial Manipulation. - Jiazhi Guan; Yi Zhao 011; Zhuoer Xu; Changhua Meng; Ke Xu 002; Youjian Zhao (AAAI, 2024)

Enhancing Distantly Supervised Named Entity Recognition with Strong Label Guided Lottery Training. - Zhiyuan Ma; Jintao Du; Changhua Meng; Weiqiang Wang 002 (LREC/COLING, 2024)

Mirror-Consistency: Harnessing Inconsistency in Majority Voting. - Siyuan Huang 003; Zhiyuan Ma; Jintao Du; Changhua Meng; Weiqiang Wang 002; Zhouhan Lin (EMNLP (Findings), 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 001 (ICLR, 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 002; Liang Chen 001 (KDD, 2024)

PC2: Pseudo-Classification Based Pseudo-Captioning for Noisy Correspondence Learning in Cross-Modal Retrieval. - Yue Duan; Zhangxuan Gu; Zhenzhe Ying; Lei Qi 001; Changhua Meng; Yinghuan Shi (ACM Multimedia, 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 002 (ECML/PKDD (10), 2024)

TroubleLLM: Align to Red Team Expert. - Zhuoer Xu; Jianping Zhang 002; Shiwen Cui; Changhua Meng; Weiqiang Wang 002 (CoRR, 2024)

E-ANT: A Large-Scale Dataset for Efficient Automatic GUI NavigaTion. - Ke Wang 042; Tianyu Xia; Zhangxuan Gu; Yi Zhao 011; Shuheng Shen; Changhua Meng; Weiqiang Wang 002; Ke Xu 002 (CoRR, 2024)

Gumbel Reranking: Differentiable End-to-End Reranker Optimization. - Siyuan Huang 003; Zhiyuan Ma; Jintao Du; Changhua Meng; Weiqiang Wang; Jingwen Leng; Minyi Guo; Zhouhan Lin (ACL (1), 2025)

Parameter-free and Accessible Prompt Learning to Enhance Adversarial Robustness for Pre-trained Vision-Language Models. - Xingran Zhou; Kun Yang; Changtao Miao; Bingyu Hu; Zhuoer Xu; Shiwen Cui; Changhua Meng; Dan Hong (NAACL (Long Papers), 2025)

Exploring Hypergraph Condensation via Variational Hyperedge Generation and Multi-Aspectual Amelioration. - Zheng Gong 001; Shuheng Shen; Changhua Meng; Ying Sun 006 (WWW, 2025)

Gumbel Reranking: Differentiable End-to-End Reranker Optimization. - Siyuan Huang 003; Zhiyuan Ma; Jintao Du; Changhua Meng; Weiqiang Wang 002; Jingwen Leng; Minyi Guo; Zhouhan Lin (CoRR, 2025)

Agent Safety Alignment via Reinforcement Learning. - Zeyang Sha; Hanling Tian; Zhuoer Xu; Shiwen Cui; Changhua Meng; Weiqiang Wang 002 (CoRR, 2025)

GUI-G2: Gaussian Reward Modeling for GUI Grounding. - Fei Tang; Zhangxuan Gu; Zhengxi Lu; Xuyang Liu; Shuheng Shen; Changhua Meng; Wen Wang 009; Wenqi Zhang 001; Yongliang Shen 001; Weiming Lu 001; Jun Xiao 001; Yueting Zhuang (CoRR, 2025)

Careful Queries, Credible Results: Teaching RAG Models Advanced Web Search Tools with Reinforcement Learning. - Yuqin Dai; Shuo Yang; Guoqing Wang; Yong Deng; Zhanwei Zhang; Jun Yin; Pengyu Zeng; Zhenzhe Ying; Changhua Meng; Can Yi; Yuchen Zhou; Weiqiang Wang; et al. (CoRR, 2025)

UI-Venus Technical Report: Building High-performance UI Agents with RFT. - Zhangxuan Gu; Zhengwen Zeng; Zhenyu Xu; Xingran Zhou; Shuheng Shen; Yunfei Liu; Beitong Zhou; Changhua Meng; Tianyu Xia; Weizhi Chen; Yue Wen; Jingya Dou; et al. (CoRR, 2025)

Atom-Searcher: Enhancing Agentic Deep Research via Fine-Grained Atomic Thought Reward. - Yong Deng; Guoqing Wang; Zhenzhe Ying; Xiaofeng Wu; Jinzhen Lin; Wenwen Xiong; Yuqin Dai; Shuo Yang; Zhanwei Zhang; Qiwen Wang; Yang Qin; Yuan Wang; et al. (CoRR, 2025)