An improved K-nearest-neighbor algorithm for text categorization. - Shengyi Jiang; Guansong Pang; Meiling Wu; Limin Kuang (Expert Syst. Appl., 2012)

A Simple Integration of Social Relationship and Text Data for Identifying Potential Customers in Microblogging. - Guansong Pang; Shengyi Jiang; Dongyi Chen (ADMA (1), 2013)

An effective class-centroid-based dimension reduction method for text classification. - Guansong Pang; Huidong Jin 001; Shengyi Jiang (WWW (Companion Volume), 2013)

A generalized cluster centroid based classifier for text categorization. - Guansong Pang; Shengyi Jiang (Inf. Process. Manag., 2013)

LeSiNN: Detecting Anomalies by Identifying Least Similar Nearest Neighbours. - Guansong Pang; Kai Ming Ting; David W. Albrecht (ICDM Workshops, 2015)

CenKNN: a scalable and effective text classifier. - Guansong Pang; Huidong Jin 001; Shengyi Jiang (Data Min. Knowl. Discov., 2015)

Unsupervised Feature Selection for Outlier Detection by Modelling Hierarchical Value-Feature Couplings. - Guansong Pang; Longbing Cao; Ling Chen 006; Huan Liu 001 (ICDM, 2016)

Outlier Detection in Complex Categorical Data by Modeling the Feature Value Couplings. - Guansong Pang; Longbing Cao; Ling Chen 006 (IJCAI, 2016)

ZERO++: Harnessing the Power of Zero Appearances to Detect Anomalies in Large-Scale Data Sets. - Guansong Pang; Kai Ming Ting; David W. Albrecht; Huidong Jin 001 (J. Artif. Intell. Res., 2016)

Selective Value Coupling Learning for Detecting Outliers in High-Dimensional Categorical Data. - Guansong Pang; Hongzuo Xu; Longbing Cao; Wentao Zhao (CIKM, 2017)

Embedding-based Representation of Categorical Data by Hierarchical Value Coupling Learning. - Songlei Jian; Longbing Cao; Guansong Pang; Kai Lu 001; Hang Gao (IJCAI, 2017)

Learning Homophily Couplings from Non-IID Data for Joint Feature Selection and Noise-Resilient Outlier Detection. - Guansong Pang; Longbing Cao; Ling Chen 006; Huan Liu 001 (IJCAI, 2017)

Sparse Modeling-Based Sequential Ensemble Learning for Effective Outlier Detection in High-Dimensional Numeric Data. - Guansong Pang; Longbing Cao; Ling Chen 006; Defu Lian; Huan Liu 001 (AAAI, 2018)

Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection. - Guansong Pang; Longbing Cao; Ling Chen 006; Huan Liu 001 (KDD, 2018)

Deep Anomaly Detection with Deviation Networks. - Guansong Pang; Chunhua Shen; Anton van den Hengel (KDD, 2019)

Deep Hashing by Discriminating Hard Examples. - Cheng Yan; Guansong Pang; Xiao Bai 001; Chunhua Shen; Jun Zhou 001; Edwin R. Hancock (ACM Multimedia, 2019)

Weakly-supervised Deep Anomaly Detection with Pairwise Relation Learning. - Guansong Pang; Anton van den Hengel; Chunhua Shen (CoRR, 2019)

Unified Multifaceted Feature Learning for Person Re-Identification. - Cheng Yan; Guansong Pang; Xiao Bai 001; Chunhua Shen (CoRR, 2019)

CURE: Flexible Categorical Data Representation by Hierarchical Coupling Learning. - Songlei Jian; Guansong Pang; Longbing Cao; Kai Lu 001; Hang Gao (IEEE Trans. Knowl. Data Eng., 2019)

Non-IID outlier detection with coupled outlier factors - Guansong Pang (2019)

Self-Trained Deep Ordinal Regression for End-to-End Video Anomaly Detection. - Guansong Pang; Cheng Yan; Chunhua Shen; Anton van den Hengel; Xiao Bai 001 (CVPR, 2020)

Unsupervised Representation Learning by Predicting Random Distances. - Hu Wang 005; Guansong Pang; Chunhua Shen; Congbo Ma (IJCAI, 2020)

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 (PAKDD (2), 2020)

Learning transferable deep convolutional neural networks for the classification of bacterial virulence factors. - Dandan Zheng; Guansong Pang; Bo Liu 055; Lihong Chen; Jian Yang 007 (Bioinform., 2020)

Deep Reinforcement Learning for Unknown Anomaly Detection. - Guansong Pang; Anton van den Hengel; Chunhua Shen; Longbing Cao (CoRR, 2020)

Beyond Triplet Loss: Person Re-identification with Fine-grained Difference-aware Pairwise Loss. - Cheng Yan; Guansong Pang; Xiao Bai 001; Jun Zhou 001; Lin Gu 003 (CoRR, 2020)

Deep Multi-task Learning for Depression Detection and Prediction in Longitudinal Data. - Guansong Pang; Ngoc Thien Anh Pham; Emma Baker; Rebecca Bentley; Anton van den Hengel (CoRR, 2020)

Heterogeneous Univariate Outlier Ensembles in Multidimensional Data. - Guansong Pang; Longbing Cao (ACM Trans. Knowl. Discov. Data, 2020)

Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning. - Yu Tian 001; Guansong Pang; Yuanhong Chen; Rajvinder Singh; Johan W. Verjans; Gustavo Carneiro 001 (ICCV, 2021)

Occluded Person Re-Identification with Single-scale Global Representations. - Cheng Yan; Guansong Pang; Jile Jiao; Xiao Bai 001; Xuetao Feng; Chunhua Shen (ICCV, 2021)

BV-Person: A Large-scale Dataset for Bird-view Person Re-identification. - Cheng Yan; Guansong Pang; Lei Wang 001; Jile Jiao; Xuetao Feng; Chunhua Shen; Jingjing Li (ICCV, 2021)

Toward Explainable Deep Anomaly Detection. - Guansong Pang; Charu C. Aggarwal (KDD, 2021)

Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly Data. - Guansong Pang; Anton van den Hengel; Chunhua Shen; Longbing Cao (KDD, 2021)

Anomaly and Novelty Detection, Explanation, and Accommodation (ANDEA). - Guansong Pang; Jundong Li; Anton van den Hengel; Longbing Cao; Thomas G. Dietterich (KDD, 2021)

Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images. - Yu Tian 001; Guansong Pang; Fengbei Liu; Yuanhong Chen; Seon-Ho Shin; Johan W. Verjans; Rajvinder Singh; Gustavo Carneiro 001 (MICCAI (5), 2021)

Deep Learning for Anomaly Detection: Challenges, Methods, and Opportunities. - Guansong Pang; Longbing Cao; Charu Aggarwal 001 (WSDM, 2021)

Weakly-supervised Video Anomaly Detection with Contrastive Learning of Long and Short-range Temporal Features. - Yu Tian 001; Guansong Pang; Yuanhong Chen; Rajvinder Singh; Johan W. Verjans; Gustavo Carneiro 001 (CoRR, 2021)

Unsupervised Anomaly Detection and Localisation with Multi-scale Interpolated Gaussian Descriptors. - Yuanhong Chen; Yu Tian 001; Guansong Pang; Gustavo Carneiro 001 (CoRR, 2021)

DRAM Failure Prediction in AIOps: EmpiricalEvaluation, Challenges and Opportunities. - Zhiyue Wu; Hongzuo Xu; Guansong Pang; Fengyuan Yu; Yijie Wang 001; Songlei Jian; Yongjun Wang (CoRR, 2021)

Explainable Deep Few-shot Anomaly Detection with Deviation Networks. - Guansong Pang; Choubo Ding; Chunhua Shen; Anton van den Hengel (CoRR, 2021)

Multi-centred Strong Augmentation via Contrastive Learning for Unsupervised Lesion Detection and Segmentation. - Yu Tian 001; Fengbei Liu; Guansong Pang; Yuanhong Chen; Yuyuan Liu; Johan W. Verjans; Rajvinder Singh; Gustavo Carneiro 001 (CoRR, 2021)

Homophily outlier detection in non-IID categorical data. - Guansong Pang; Longbing Cao; Ling Chen 006 (Data Min. Knowl. Discov., 2021)

Guest Editorial: Non-IID Outlier Detection in Complex Contexts. - Guansong Pang; Fabrizio Angiulli; Mihai Cucuringu; Huan Liu 001 (IEEE Intell. Syst., 2021)

Viral Pneumonia Screening on Chest X-Rays Using Confidence-Aware Anomaly Detection. - Jianpeng Zhang; Yutong Xie 001; Guansong Pang; Zhibin Liao; Johan Verjans; Wenxing Li; Zongji Sun; Jian He; Yi Li; Chunhua Shen; Yong Xia 001 (IEEE Trans. Medical Imaging, 2021)

Deep One-Class Classification via Interpolated Gaussian Descriptor. - Yuanhong Chen; Yu Tian 001; Guansong Pang; Gustavo Carneiro 001 (AAAI, 2022)

Catching Both Gray and Black Swans: Open-set Supervised Anomaly Detection. - Choubo Ding; Guansong Pang; Chunhua Shen (CVPR, 2022)

Pixel-Wise Energy-Biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes. - Yu Tian 001; Yuyuan Liu; Guansong Pang; Fengbei Liu; Yuanhong Chen; Gustavo Carneiro 001 (ECCV (39), 2022)

ANDEA: Anomaly and Novelty Detection, Explanation, and Accommodation. - Guansong Pang; Jundong Li; Anton van den Hengel; Longbing Cao; Thomas G. Dietterich (KDD, 2022)

Contrastive Transformer-Based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection. - Yu Tian 001; Guansong Pang; Fengbei Liu; Yuyuan Liu; Chong Wang 012; Yuanhong Chen; Johan Verjans; Gustavo Carneiro 001 (MICCAI (3), 2022)

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 (PAKDD (2), 2022)

Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation. - Rongrong Ma; Guansong Pang; Ling Chen 006; Anton van den Hengel (WSDM, 2022)

Deep Learning for Hate Speech Detection: A Comparative Study. - Jitendra Singh Malik; Guansong Pang; Anton van den Hengel (CoRR, 2022)

Unsupervised Anomaly Detection in Medical Images with a Memory-augmented Multi-level Cross-attentional Masked Autoencoder. - Yu Tian 001; Guansong Pang; Yuyuan Liu; Chong Wang 012; Yuanhong Chen; Fengbei Liu; Rajvinder Singh; Johan W. Verjans; Gustavo Carneiro 001 (CoRR, 2022)

Deep Learning for Anomaly Detection: A Review. - Guansong Pang; Chunhua Shen; Longbing Cao; Anton van den Hengel (ACM Comput. Surv., 2022)

AI in Beijing 2022 Olympic Winter Games. - Guansong Pang (IEEE Intell. Syst., 2022)

The AI Chip Race. - Guansong Pang (IEEE Intell. Syst., 2022)

Artificial Intelligence for Natural Disaster Management. - Guansong Pang (IEEE Intell. Syst., 2022)

Joint hyperbolic and Euclidean geometry contrastive graph neural networks. - Xiaoyu Xu; Guansong Pang; Di Wu 056; Mingsheng Shang 001 (Inf. Sci., 2022)

An efficient annealing-assisted differential evolution for multi-parameter adaptive latent factor analysis. - Qing Li 035; Guansong Pang; Mingsheng Shang 001 (J. Big Data, 2022)

Beyond Triplet Loss: Person Re-Identification With Fine-Grained Difference-Aware Pairwise Loss. - Cheng Yan; Guansong Pang; Xiao Bai 001; Changhong Liu; Xin Ning 001; Lin Gu 003; Jun Zhou 001 (IEEE Trans. Multim., 2022)

Editorial Deep Learning for Anomaly Detection. - Guansong Pang; Charu Aggarwal 001; Chunhua Shen; Nicu Sebe (IEEE Trans. Neural Networks Learn. Syst., 2022)

Cross-Domain Graph Anomaly Detection via Anomaly-Aware Contrastive Alignment. - Qizhou Wang 001; Guansong Pang; Mahsa Salehi; Wray L. Buntine; Christopher Leckie (AAAI, 2023)

Glocal Energy-based Learning for Few-Shot Open-Set Recognition. - Haoyu Wang 016; Guansong Pang; Peng Wang 023; Lei Zhang 054; Wei Wei 008; Yanning Zhang 001 (CVPR, 2023)

HRGCN: Heterogeneous Graph-level Anomaly Detection with Hierarchical Relation-augmented Graph Neural Networks. - Jiaxi Li; Guansong Pang; Ling Chen 006; Mohammad-Reza Namazi-Rad (DSAA, 2023)

Anomaly Detection under Distribution Shift. - Tri Cao; Jiawen Zhu; Guansong Pang (ICCV, 2023)

Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentation. - Yuyuan Liu; Choubo Ding; Yu Tian 001; Guansong Pang; Vasileios Belagiannis; Ian D. Reid 001; Gustavo Carneiro 001 (ICCV, 2023)

Feature Prediction Diffusion Model for Video Anomaly Detection. - Cheng Yan; Shiyu Zhang; Yang Liu 357; Guansong Pang; Wenjun Wang (ICCV, 2023)

Deep Weakly-supervised Anomaly Detection. - Guansong Pang; Chunhua Shen; Huidong Jin 001; Anton van den Hengel (KDD, 2023)

Unsupervised Anomaly Detection in Medical Images with a Memory-Augmented Multi-level Cross-Attentional Masked Autoencoder. - Yu Tian 001; Guansong Pang; Yuyuan Liu; Chong Wang 012; Yuanhong Chen; Fengbei Liu; Rajvinder Singh; Johan W. Verjans; Mengyu Wang 001; Gustavo Carneiro 001 (MLMI@MICCAI (2), 2023)

Truncated Affinity Maximization: One-class Homophily Modeling for Graph Anomaly Detection. - Hezhe Qiao; Guansong Pang (NeurIPS, 2023)

Graph-Level Anomaly Detection via Hierarchical Memory Networks. - Chaoxi Niu; Guansong Pang; Ling Chen 006 (ECML/PKDD (1), 2023)

Subgraph Centralization: A Necessary Step for Graph Anomaly Detection. - Zhong Zhuang; Kai Ming Ting; Guansong Pang; Shuaibin Song (SDM, 2023)

International Workshop on Learning with Knowledge Graphs: Construction, Embedding, and Reasoning. - Qing Li 001; Xiao Huang 001; Ninghao Liu; Yuxiao Dong; Guansong Pang (WSDM, 2023)

Background Matters: Enhancing Out-of-distribution Detection with Domain Features. - Choubo Ding; Guansong Pang; Chunhua Shen (CoRR, 2023)

Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects. - Kexin Zhang 007; Qingsong Wen; Chaoli Zhang 001; Rongyao Cai; Ming Jin 005; Yong Liu 007; James Zhang; Yuxuan Liang; Guansong Pang; Dongjin Song; Shirui Pan (CoRR, 2023)

Unsupervised Recognition of Unknown Objects for Open-World Object Detection. - Ruohuan Fang; Guansong Pang; Lei Zhou 008; Xiao Bai 001; Jin Zheng (CoRR, 2023)

LARA: A Light and Anti-overfitting Retraining Approach for Unsupervised Anomaly Detection. - Feiyi Chen; Zhen Qing; Yingying Zhang; Shuiguang Deng; Yi Xiao; Guansong Pang; Qingsong Wen (CoRR, 2023)

Open-Set Graph Anomaly Detection via Normal Structure Regularisation. - Qizhou Wang 001; Guansong Pang; Mahsa Salehi; Wray L. Buntine; Christopher Leckie (CoRR, 2023)

MIRROR: Mining Implicit Relationships via Structure-Enhanced Graph Convolutional Networks. - Jiaying Liu 006; Feng Xia 001; Jing Ren 001; Bo Xu 008; Guansong Pang; Lianhua Chi (ACM Trans. Knowl. Discov. Data, 2023)

RoSAS: Deep semi-supervised anomaly detection with contamination-resilient continuous supervision. - Hongzuo Xu; Yijie Wang 001; Guansong Pang; Songlei Jian; Ning Liu 015; Yongjun Wang (Inf. Process. Manag., 2023)

Self-supervised pseudo multi-class pre-training for unsupervised anomaly detection and segmentation in medical images. - Yu Tian 001; Fengbei Liu; Guansong Pang; Yuanhong Chen; Yuyuan Liu; Johan W. Verjans; Rajvinder Singh; Gustavo Carneiro 001 (Medical Image Anal., 2023)

Deep Isolation Forest for Anomaly Detection. - Hongzuo Xu; Guansong Pang; Yijie Wang 001; Yongjun Wang (IEEE Trans. Knowl. Data Eng., 2023)

Simple Image-Level Classification Improves Open-Vocabulary Object Detection. - Ruohuan Fang; Guansong Pang; Xiao Bai 001 (AAAI, 2024)

Out-of-Distribution Detection in Long-Tailed Recognition with Calibrated Outlier Class Learning. - Wenjun Miao; Guansong Pang; Xiao Bai 001; Tianqi Li; Jin Zheng (AAAI, 2024)

VadCLIP: Adapting Vision-Language Models for Weakly Supervised Video Anomaly Detection. - Peng Wu 015; Xuerong Zhou; Guansong Pang; Lingru Zhou; Qingsen Yan; Peng Wang 015; Yanning Zhang 001 (AAAI, 2024)

Learning Transferable Negative Prompts for Out-of-Distribution Detection. - Tianqi Li; Guansong Pang; Xiao Bai 001; Wenjun Miao; Jin Zheng (CVPR, 2024)

Open-Vocabulary Video Anomaly Detection. - Peng Wu 015; Xuerong Zhou; Guansong Pang; Yujia Sun; Jing Liu 006; Peng Wang 015; Yanning Zhang 001 (CVPR, 2024)

Anomaly Heterogeneity Learning for Open-Set Supervised Anomaly Detection. - Jiawen Zhu; Choubo Ding; Yu Tian 001; Guansong Pang (CVPR, 2024)

Toward Generalist Anomaly Detection via In-Context Residual Learning with Few-Shot Sample Prompts. - Jiawen Zhu; Guansong Pang (CVPR, 2024)

Graph Continual Learning with Debiased Lossless Memory Replay. - Chaoxi Niu; Guansong Pang; Ling Chen 006 (ECAI, 2024)

Unraveling the 'Anomaly' in Time Series Anomaly Detection: A Self-supervised Tri-domain Solution. - Yuting Sun; Guansong Pang; Guanhua Ye; Tong Chen 005; Xia Hu 001; Hongzhi Yin (ICDE, 2024)

AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection. - Qihang Zhou; Guansong Pang; Yu Tian 001; Shibo He; Jiming Chen 001 (ICLR, 2024)

Zero-Shot Out-of-Distribution Detection with Outlier Label Exposure. - Choubo Ding; Guansong Pang (IJCNN, 2024)

Imbalanced Graph Classification with Multi-scale Oversampling Graph Neural Networks. - Rongrong Ma; Guansong Pang; Ling Chen 006 (IJCNN, 2024)

Cluster-Wide Task Slowdown Detection in Cloud System. - Feiyi Chen; Yingying Zhang; Lunting Fan; Yuxuan Liang; Guansong Pang; Qingsong Wen; Shuiguang Deng (KDD, 2024)

Improving Out-of-Distribution Detection with Disentangled Foreground and Background Features. - Choubo Ding; Guansong Pang (ACM Multimedia, 2024)

Weakly Supervised Video Anomaly Detection and Localization with Spatio-Temporal Prompts. - Peng Wu 015; Xuerong Zhou; Guansong Pang; Zhiwei Yang; Qingsen Yan; Peng Wang 015; Yanning Zhang 001 (ACM Multimedia, 2024)

Long-Tailed Out-of-Distribution Detection via Normalized Outlier Distribution Adaptation. - Wenjun Miao; Guansong Pang; Jin Zheng; Xiao Bai 001 (NeurIPS, 2024)

Replay-and-Forget-Free Graph Class-Incremental Learning: A Task Profiling and Prompting Approach. - Chaoxi Niu; Guansong Pang; Ling Chen 006; Bing Liu (NeurIPS, 2024)

Generative Semi-supervised Graph Anomaly Detection. - Hezhe Qiao; Qingsong Wen; Xiaoli Li 001; Ee-Peng Lim; Guansong Pang (NeurIPS, 2024)

Self-supervised Spatial-Temporal Normality Learning for Time Series Anomaly Detection. - Yutong Chen; Hongzuo Xu; Guansong Pang; Hezhe Qiao; Yuan Zhou; Mingsheng Shang 001 (ECML/PKDD (6), 2024)

LARA: A Light and Anti-overfitting Retraining Approach for Unsupervised Time Series Anomaly Detection. - Feiyi Chen; Zhen Qin 004; Mengchu Zhou; Yingying Zhang; Shuiguang Deng; Lunting Fan; Guansong Pang; Qingsong Wen (WWW, 2024)

A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect. - Yunkang Cao; Xiaohao Xu; Jiangning Zhang; Yuqi Cheng; Xiaonan Huang; Guansong Pang; Weiming Shen 001 (CoRR, 2024)

Learning Feature Inversion for Multi-class Anomaly Detection under General-purpose COCO-AD Benchmark. - Jiangning Zhang; Chengjie Wang; Xiangtai Li; Guanzhong Tian; Zhucun Xue; Yong Liu 007; Guansong Pang; Dacheng Tao (CoRR, 2024)

OpenCIL: Benchmarking Out-of-Distribution Detection in Class-Incremental Learning. - Wenjun Miao; Guansong Pang; Trong-Tung Nguyen; Ruohang Fang; Jin Zheng; Xiao Bai 001 (CoRR, 2024)

Deep Learning for Video Anomaly Detection: A Review. - Peng Wu 015; Chengyu Pan; Yuting Yan; Guansong Pang; Peng Wang 015; Yanning Zhang 001 (CoRR, 2024)

Fine-grained Abnormality Prompt Learning for Zero-shot Anomaly Detection. - Jiawen Zhu; Yew-Soon Ong; Chunhua Shen; Guansong Pang (CoRR, 2024)

Abnormality Forecasting: Time Series Anomaly Prediction via Future Context Modeling. - Sinong Zhao; Wenrui Wang; Hongzuo Xu; Zhaoyang Yu; Qingsong Wen; Gang Wang 001; Xiaoguang Liu 001; Guansong Pang (CoRR, 2024)

Zero-shot Generalist Graph Anomaly Detection with Unified Neighborhood Prompts. - Chaoxi Niu; Hezhe Qiao; Changlu Chen; Ling Chen 006; Guansong Pang (CoRR, 2024)

GrokFormer: Graph Fourier Kolmogorov-Arnold Transformers. - Guoguo Ai; Guansong Pang; Hezhe Qiao; Yuan Gao; Hui Yan (CoRR, 2024)

Harnessing collective structure knowledge in data augmentation for graph neural networks. - Rongrong Ma; Guansong Pang; Ling Chen 006 (Neural Networks, 2024)

Learning adversarial semantic embeddings for zero-shot recognition in open worlds. - Tianqi Li; Guansong Pang; Xiao Bai 001; Jin Zheng; Lei Zhou 008; Xin Ning 001 (Pattern Recognit., 2024)

Affinity Uncertainty-Based Hard Negative Mining in Graph Contrastive Learning. - Chaoxi Niu; Guansong Pang; Ling Chen 006 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects. - Kexin Zhang 007; Qingsong Wen; Chaoli Zhang 001; Rongyao Cai; Ming Jin 005; Yong Liu 007; James Y. Zhang; Yuxuan Liang; Guansong Pang; Dongjin Song; Shirui Pan (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Calibrated One-Class Classification for Unsupervised Time Series Anomaly Detection. - Hongzuo Xu; Yijie Wang 001; Songlei Jian; Qing Liao 001; Yongjun Wang; Guansong Pang (IEEE Trans. Knowl. Data Eng., 2024)

HVI: A New Color Space for Low-light Image Enhancement. - Qingsen Yan; Yixu Feng; Cheng Zhang; Guansong Pang; Kangbiao Shi; Peng Wu 015; Wei Dong 010; Jinqiu Sun; Yanning Zhang 001 (CVPR, 2025)

Open-Set Graph Anomaly Detection via Normal Structure Regularisation. - Qizhou Wang 001; Guansong Pang; Mahsa Salehi; Xiaokun Xia; Christopher Leckie (ICLR, 2025)

Adapting Large Language Models for Parameter-Efficient Log Anomaly Detection. - Ying Fu Lim; Jiawen Zhu; Guansong Pang (PAKDD (7), 2025)

Adaptive Deviation Learning for Visual Anomaly Detection with Data Contamination. - Anindya Sundar Das 002; Guansong Pang; Monowar H. Bhuyan (WACV, 2025)

What Are Anomalies in a Network? - Kai Ming Ting; Zhong Zhuang; Guansong Pang; Zongyou Liu; Tianrun Liang; Qiuran Zhao (ACM Trans. Knowl. Discov. Data, 2025)

Synergizing Large Language Models and Task-specific Models for Time Series Anomaly Detection. - Feiyi Chen; Leilei Zhang; Guansong Pang; Roger Zimmermann; Shuiguang Deng (CoRR, 2025)

AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly Detection. - Hezhe Qiao; Chaoxi Niu; Ling Chen 006; Guansong Pang (CoRR, 2025)

DOEI: Dual Optimization of Embedding Information for Attention-Enhanced Class Activation Maps. - Hongjie Zhu; Zeyu Zhang; Guansong Pang; Xu Wang; Shimin Wen; Yu Bai; Daji Ergu; Ying Cai; Yang Zhao (CoRR, 2025)

AssistPDA: An Online Video Surveillance Assistant for Video Anomaly Prediction, Detection, and Analysis. - Zhiwei Yang; Chen Gao; Jing Liu 006; Peng Wu 015; Guansong Pang; Mike Zheng Shou (CoRR, 2025)

AVadCLIP: Audio-Visual Collaboration for Robust Video Anomaly Detection. - Peng Wu 015; Wanshun Su; Guansong Pang; Yujia Sun; Qingsen Yan; Peng Wang 015; Yanning Zhang 001 (CoRR, 2025)

Robust Hallucination Detection in LLMs via Adaptive Token Selection. - Mengjia Niu; Hamed Haddadi; Guansong Pang (CoRR, 2025)

SlowFastVAD: Video Anomaly Detection via Integrating Simple Detector and RAG-Enhanced Vision-Language Model. - Zongcan Ding; Haodong Zhang; Peng Wu 015; Guansong Pang; Zhiwei Yang; Peng Wang 015; Yanning Zhang 001 (CoRR, 2025)

Semi-supervised Graph Anomaly Detection via Robust Homophily Learning. - Guoguo Ai; Hezhe Qiao; Hui Yan; Guansong Pang (CoRR, 2025)

Unsupervised Recognition of Unknown Objects for Open-World Object Detection. - Ruohuan Fang; Guansong Pang; Wenjun Miao; Xiao Bai 001; Jin Zheng; Xin Ning 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)

HVI-CIDNet+: Beyond Extreme Darkness for Low-Light Image Enhancement. - Qingsen Yan; Kangbiao Shi; Yixu Feng; Tao Hu; Peng Wu 015; Guansong Pang; Yanning Zhang 001 (CoRR, 2025)

CoLeCLIP: Open-Domain Continual Learning via Joint Task Prompt and Vocabulary Learning. - Yukun Li; Guansong Pang; Wei Suo; Chenchen Jing; Yuling Xi; Lingqiao Liu; Hao Chen 041; Guoqiang Liang 001; Peng Wang 015 (IEEE Trans. Neural Networks Learn. Syst., 2025)

Deep Graph Anomaly Detection: A Survey and New Perspectives. - Hezhe Qiao; Hanghang Tong; Bo An 001; Irwin King; Charu Aggarwal 001; Guansong Pang (IEEE Trans. Knowl. Data Eng., 2025)

OpenCIL: Benchmarking out-of-distribution detection in class incremental learning. - Wenjun Miao; Guansong Pang; Trong-Tung Nguyen; Ruohuan Fang; Jin Zheng; Xiao Bai 001 (Pattern Recognit., 2026)