BAARD: Blocking Adversarial Examples by Testing for Applicability, Reliability and Decidability. - Xinglong Chang; Katharina Dost; Kaiqi Zhao 001; Ambra Demontis; Fabio Roli; Gillian Dobbie; Jörg Wicker (PAKDD (1), 2023)

Targeted Attacks on Time Series Forecasting. - Zeyu Chen; Katharina Dost; Xuan Zhu; Xinglong Chang; Gillian Dobbie; Jörg Wicker (PAKDD (4), 2023)

Memento: Facilitating Effortless, Efficient, and Reliable ML Experiments. - Zac Pullar-Strecker; Xinglong Chang; Liam Brydon; Ioannis Ziogas; Katharina Dost; Jörg Wicker (ECML/PKDD (7), 2023)

Fast Adversarial Label-Flipping Attack on Tabular Data. - Xinglong Chang; Gillian Dobbie; Jörg Wicker (CoRR, 2023)

Poison is Not Traceless: Fully-Agnostic Detection of Poisoning Attacks. - Xinglong Chang; Katharina Dost; Gillian Dobbie; Jörg Wicker (CoRR, 2023)

Feature-Structure Adaptive Completion Graph Neural Network for Cold-start Recommendation. - Songyuan Lei; Xinglong Chang; Zhizhi Yu; Dongxiao He; Cuiying Huo; Jianrong Wang; Di Jin 001 (AAAI, 2025)

Dynamic Neighborhood Modeling via Node-Subgraph Contrastive Learning for Graph-Based Fraud Detection. - Zhizhi Yu; Chundong Liang; Xinglong Chang; Dongxiao He; Di Jin 001; Jianguo Wei (AAAI, 2025)

FitCLM: LLM-Augmented Candidate-aware Cross-view Contrastive Learning for Person-Job Fit. - Gaozhi Tang; Jianrong Wang; Xinglong Chang; Di Jin 001; Xiudong Han (CSCWD, 2025)

Hypergraph Collaborative Filtering With Adaptive Augmentation of Graph Data for Recommendation. - Jian Wang; Jianrong Wang; Di Jin 001; Xinglong Chang (IEEE Trans. Knowl. Data Eng., 2025)

M-Graphormer: Multi-Channel Graph Transformer for Node Representation Learning. - Xinglong Chang; Jianrong Wang; Mingxiang Wen; Yingkui Wang; Yuxiao Huang (IEEE Trans. Big Data, 2025)