| 2026 | AAAI | MTAttack: Multi-Target Backdoor Attacks Against Large Vision-Language Models. | Zihan Wang, Guansong Pang, Wenjun Miao, Jin Zheng, Xiao Bai |
| 2026 | AAAI | TargetVAU: Multimodal Anomaly-Aware Reasoning for Target Behavior Understanding in Videos. | Lingru Zhou, Peng Wu, Manqing Zhang, Qingsheng Wang, Guansong Pang, Peng Wang |
| 2026 | WWW | Robust Graph Learning on the Web: Challenges, Methods, and Applications. | Xiang Ao, Yang Liu, Guansong Pang, Yuanhao Ding, Hezhe Qiao, Dawei Cheng, Qing He |
| 2025 | CIKM | MetaCAN: Improving Generalizability of Few-shot Anomaly Detection with Meta-learning. | Zhisheng Lv, Jianfeng Zhang, Songlei Jian, Chenlin Huang, Hongguang Zhang, Guansong Pang, Zhong Liu |
| 2025 | CVPR | HVI: A New Color Space for Low-light Image Enhancement. | Qingsen Yan, Yixu Feng, Cheng Zhang, Guansong Pang, Kangbiao Shi, Peng Wu, Wei Dong, Jinqiu Sun, Yanning Zhang |
| 2025 | ICCV | Auxiliary Prompt Tuning of Vision-Language Models for Few-Shot Out-of-Distribution Detection. | Wenjun Miao, Guansong Pang, Zihan Wang, Jin Zheng, Xiao Bai |
| 2025 | ICCV | Fine-Grained Abnormality Prompt Learning for Zero-Shot Anomaly Detection. | Jiawen Zhu, Yew-Soon Ong, Chunhua Shen, Guansong Pang |
| 2025 | ICLR | Open-Set Graph Anomaly Detection via Normal Structure Regularisation. | Qizhou Wang, Guansong Pang, Mahsa Salehi, Xiaokun Xia, Christopher Leckie |
| 2025 | ICML | Information Bottleneck-guided MLPs for Robust Spatial-temporal Forecasting. | Min Chen, Guansong Pang, Wenjun Wang, Cheng Yan |
| 2025 | ICML | GrokFormer: Graph Fourier Kolmogorov-Arnold Transformers. | GuoguoAi, Guansong Pang, Hezhe Qiao, Yuan Gao, Hui Yan |
| 2025 | IJCAI | Zero-shot Generalist Graph Anomaly Detection with Unified Neighborhood Prompts. | Chaoxi Niu, Hezhe Qiao, Changlu Chen, Ling Chen, Guansong Pang |
| 2025 | IJCAI | FreqLLM: Frequency-Aware Large Language Models for Time Series Forecasting. | Shunnan Wang, Min Gao, Zongwei Wang, Yibing Bai, Feng Jiang, Guansong Pang |
| 2025 | KDD | AffinityTune: A Prompt-Tuning Framework for Few-Shot Anomaly Detection on Graphs. | Jingyan Chen, Guanghui Zhu, Guansong Pang, Chunfeng Yuan, Yihua Huang |
| 2025 | KDD | AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly Detection. | Hezhe Qiao, Chaoxi Niu, Ling Chen, Guansong Pang |
| 2025 | PAKDD | Adapting Large Language Models for Parameter-Efficient Log Anomaly Detection. | Ying Fu Lim, Jiawen Zhu, Guansong Pang |
| 2025 | WACV | Adaptive Deviation Learning for Visual Anomaly Detection with Data Contamination. | Anindya Sundar Das, Guansong Pang, Monowar Bhuyan |
| 2024 | AAAI | Simple Image-Level Classification Improves Open-Vocabulary Object Detection. | Ruohuan Fang, Guansong Pang, Xiao Bai |
| 2024 | AAAI | Out-of-Distribution Detection in Long-Tailed Recognition with Calibrated Outlier Class Learning. | Wenjun Miao, Guansong Pang, Xiao Bai, Tianqi Li, Jin Zheng |
| 2024 | AAAI | VadCLIP: Adapting Vision-Language Models for Weakly Supervised Video Anomaly Detection. | Peng Wu, Xuerong Zhou, Guansong Pang, Lingru Zhou, Qingsen Yan, Peng Wang, Yanning Zhang |
| 2024 | CVPR | Learning Transferable Negative Prompts for Out-of-Distribution Detection. | Tianqi Li, Guansong Pang, Xiao Bai, Wenjun Miao, Jin Zheng |
| 2024 | CVPR | Open-Vocabulary Video Anomaly Detection. | Peng Wu, Xuerong Zhou, Guansong Pang, Yujia Sun, Jing Liu, Peng Wang, Yanning Zhang |
| 2024 | CVPR | Anomaly Heterogeneity Learning for Open-Set Supervised Anomaly Detection. | Jiawen Zhu, Choubo Ding, Yu Tian, Guansong Pang |
| 2024 | CVPR | Toward Generalist Anomaly Detection via In-Context Residual Learning with Few-Shot Sample Prompts. | Jiawen Zhu, Guansong Pang |
| 2024 | ECAI | Graph Continual Learning with Debiased Lossless Memory Replay. | Chaoxi Niu, Guansong Pang, Ling Chen |
| 2024 | ICDE | Unraveling the 'Anomaly' in Time Series Anomaly Detection: A Self-supervised Tri-domain Solution. | Yuting Sun, Guansong Pang, Guanhua Ye, Tong Chen, Xia Hu, Hongzhi Yin |
| 2024 | ICLR | AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection. | Qihang Zhou, Guansong Pang, Yu Tian, Shibo He, Jiming Chen |
| 2024 | IJCNN | Zero-Shot Out-of-Distribution Detection with Outlier Label Exposure. | Choubo Ding, Guansong Pang |
| 2024 | IJCNN | Imbalanced Graph Classification with Multi-scale Oversampling Graph Neural Networks. | Rongrong Ma, Guansong Pang, Ling Chen |
| 2024 | KDD | Cluster-Wide Task Slowdown Detection in Cloud System. | Feiyi Chen, Yingying Zhang, Lunting Fan, Yuxuan Liang, Guansong Pang, Qingsong Wen, Shuiguang Deng |
| 2024 | WWW | LARA: A Light and Anti-overfitting Retraining Approach for Unsupervised Time Series Anomaly Detection. | Feiyi Chen, Zhen Qin, Mengchu Zhou, Yingying Zhang, Shuiguang Deng, Lunting Fan, Guansong Pang, Qingsong Wen |
| 2023 | AAAI | Cross-Domain Graph Anomaly Detection via Anomaly-Aware Contrastive Alignment. | Qizhou Wang, Guansong Pang, Mahsa Salehi, Wray L. Buntine, Christopher Leckie |
| 2023 | CVPR | Glocal Energy-based Learning for Few-Shot Open-Set Recognition. | Haoyu Wang, Guansong Pang, Peng Wang, Lei Zhang, Wei Wei, Yanning Zhang |
| 2023 | DSAA | HRGCN: Heterogeneous Graph-level Anomaly Detection with Hierarchical Relation-augmented Graph Neural Networks. | Jiaxi Li, Guansong Pang, Ling Chen, Mohammad-Reza Namazi-Rad |
| 2023 | ICCV | Anomaly Detection under Distribution Shift. | Tri Cao, Jiawen Zhu, Guansong Pang |
| 2023 | ICCV | Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentation. | Yuyuan Liu, Choubo Ding, Yu Tian, Guansong Pang, Vasileios Belagiannis, Ian D. Reid, Gustavo Carneiro |
| 2023 | ICCV | Feature Prediction Diffusion Model for Video Anomaly Detection. | Cheng Yan, Shiyu Zhang, Yang Liu, Guansong Pang, Wenjun Wang |
| 2023 | KDD | Deep Weakly-supervised Anomaly Detection. | Guansong Pang, Chunhua Shen, Huidong Jin, Anton van den Hengel |
| 2023 | WSDM | International Workshop on Learning with Knowledge Graphs: Construction, Embedding, and Reasoning. | Qing Li, Xiao Huang, Ninghao Liu, Yuxiao Dong, Guansong Pang |
| 2023 | SDM | Subgraph Centralization: A Necessary Step for Graph Anomaly Detection. | Zhong Zhuang, Kai Ming Ting, Guansong Pang, Shuaibin Song |
| 2022 | AAAI | Deep One-Class Classification via Interpolated Gaussian Descriptor. | Yuanhong Chen, Yu Tian, Guansong Pang, Gustavo Carneiro |
| 2022 | CVPR | Catching Both Gray and Black Swans: Open-set Supervised Anomaly Detection. | Choubo Ding, Guansong Pang, Chunhua Shen |
| 2022 | ECCV | Pixel-Wise Energy-Biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes. | Yu Tian, Yuyuan Liu, Guansong Pang, Fengbei Liu, Yuanhong Chen, Gustavo Carneiro |
| 2022 | KDD | ANDEA: Anomaly and Novelty Detection, Explanation, and Accommodation. | Guansong Pang, Jundong Li, Anton van den Hengel, Longbing Cao, Thomas G. Dietterich |
| 2022 | MICCAI | Contrastive Transformer-Based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection. | Yu Tian, Guansong Pang, Fengbei Liu, Yuyuan Liu, Chong Wang, Yuanhong Chen, Johan Verjans, Gustavo Carneiro |
| 2022 | PAKDD | Deep Depression Prediction on Longitudinal Data via Joint Anomaly Ranking and Classification. | Guansong Pang, Ngoc Thien Anh Pham, Emma Baker, Rebecca Bentley, Anton van den Hengel |
| 2022 | WSDM | Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation. | Rongrong Ma, Guansong Pang, Ling Chen, Anton van den Hengel |
| 2021 | ICCV | Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning. | Yu Tian, Guansong Pang, Yuanhong Chen, Rajvinder Singh, Johan W. Verjans, Gustavo Carneiro |
| 2021 | ICCV | Occluded Person Re-Identification with Single-scale Global Representations. | Cheng Yan, Guansong Pang, Jile Jiao, Xiao Bai, Xuetao Feng, Chunhua Shen |
| 2021 | ICCV | BV-Person: A Large-scale Dataset for Bird-view Person Re-identification. | Cheng Yan, Guansong Pang, Lei Wang, Jile Jiao, Xuetao Feng, Chunhua Shen, Jingjing Li |
| 2021 | KDD | Toward Explainable Deep Anomaly Detection. | Guansong Pang, Charu C. Aggarwal |
| 2021 | KDD | Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly Data. | Guansong Pang, Anton van den Hengel, Chunhua Shen, Longbing Cao |
| 2021 | KDD | Anomaly and Novelty Detection, Explanation, and Accommodation (ANDEA). | Guansong Pang, Jundong Li, Anton van den Hengel, Longbing Cao, Thomas G. Dietterich |
| 2021 | MICCAI | Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images. | Yu Tian, Guansong Pang, Fengbei Liu, Yuanhong Chen, Seon-Ho Shin, Johan W. Verjans, Rajvinder Singh, Gustavo Carneiro |
| 2021 | WSDM | Deep Learning for Anomaly Detection: Challenges, Methods, and Opportunities. | Guansong Pang, Longbing Cao, Charu Aggarwal |
| 2020 | CVPR | Self-Trained Deep Ordinal Regression for End-to-End Video Anomaly Detection. | Guansong Pang, Cheng Yan, Chunhua Shen, Anton van den Hengel, Xiao Bai |
| 2020 | IJCAI | Unsupervised Representation Learning by Predicting Random Distances. | Hu Wang, Guansong Pang, Chunhua Shen, Congbo Ma |
| 2020 | PAKDD | Learning Discriminative Neural Sentiment Units for Semi-supervised Target-Level Sentiment Classification. | Jingjing Zhao, Yao Yang, Guansong Pang, Lei Lv, Hong Shang, Zhongqian Sun, Wei Yang |
| 2019 | KDD | Deep Anomaly Detection with Deviation Networks. | Guansong Pang, Chunhua Shen, Anton van den Hengel |
| 2018 | AAAI | Sparse Modeling-Based Sequential Ensemble Learning for Effective Outlier Detection in High-Dimensional Numeric Data. | Guansong Pang, Longbing Cao, Ling Chen, Defu Lian, Huan Liu |
| 2018 | KDD | Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection. | Guansong Pang, Longbing Cao, Ling Chen, Huan Liu |
| 2017 | CIKM | Selective Value Coupling Learning for Detecting Outliers in High-Dimensional Categorical Data. | Guansong Pang, Hongzuo Xu, Longbing Cao, Wentao Zhao |
| 2017 | IJCAI | Embedding-based Representation of Categorical Data by Hierarchical Value Coupling Learning. | Songlei Jian, Longbing Cao, Guansong Pang, Kai Lu, Hang Gao |
| 2017 | IJCAI | Learning Homophily Couplings from Non-IID Data for Joint Feature Selection and Noise-Resilient Outlier Detection. | Guansong Pang, Longbing Cao, Ling Chen, Huan Liu |
| 2016 | ICDM | Unsupervised Feature Selection for Outlier Detection by Modelling Hierarchical Value-Feature Couplings. | Guansong Pang, Longbing Cao, Ling Chen, Huan Liu |
| 2016 | IJCAI | Outlier Detection in Complex Categorical Data by Modeling the Feature Value Couplings. | Guansong Pang, Longbing Cao, Ling Chen |
| 2015 | ICDM | LeSiNN: Detecting Anomalies by Identifying Least Similar Nearest Neighbours. | Guansong Pang, Kai Ming Ting, David W. Albrecht |
| 2013 | ADMA | A Simple Integration of Social Relationship and Text Data for Identifying Potential Customers in Microblogging. | Guansong Pang, Shengyi Jiang, Dongyi Chen |
| 2013 | WWW | An effective class-centroid-based dimension reduction method for text classification. | Guansong Pang, Huidong Jin, Shengyi Jiang |