1 citations · 2 across the 8 of their papers we have counts for
9 papers
Towards Detecting AI-Assisted Responses in Online Surveys
Qizhou Wang, Bogdan Mamaev, Christopher Leckie
The use of LLMs to complete online surveys impacts the validity of survey-based research, but detecting such usage remains underexplored. We introduce an initial benchmark dataset,…
AudioMosaic: Contrastive Masked Audio Representation Learning
Hanxun Huang, Qizhou Wang, Xingjun Ma +3
Audio self-supervised learning (SSL) aims to learn general-purpose representations from large-scale unlabeled audio data. While recent advances have been driven mainly by generativ…
SurFITR: A Dataset for Surveillance Image Forgery Detection and Localisation
Qizhou Wang, Guansong Pang, Christopher Leckie
We present the Surveillance Forgery Image Test Range (SurFITR), a dataset for surveillance-style image forgery detection and localisation, in response to recent advances in open-ac…
HierCon: Hierarchical Contrastive Attention for Audio Deepfake Detection
Zhili Nicholas Liang, Soyeon Caren Han, Qizhou Wang +1
Audio deepfakes generated by modern TTS and voice conversion systems are increasingly difficult to distinguish from real speech, raising serious risks for security and online trust…
CEDL: Centre-Enhanced Discriminative Learning for Anomaly Detection
Zahra Zamanzadeh Darban, Qizhou Wang, Charu C. Aggarwal +3
Supervised anomaly detection methods perform well in identifying known anomalies that are well represented in the training set. However, they often struggle to generalise beyond th…
AUDETER: A Large-scale Dataset for Deepfake Audio Detection in Open Worlds
Qizhou Wang, Hanxun Huang, Guansong Pang +2
Speech synthesis systems can now produce highly realistic vocalisations that pose significant authenticity challenges. Despite substantial progress in deepfake detection models, th…
GenIAS: Generator for Instantiating Anomalies in time Series
Zahra Zamanzadeh Darban, Qizhou Wang, Geoffrey I. Webb +3
Synthetic anomaly injection is a recent and promising approach for time series anomaly detection (TSAD), but existing methods rely on ad hoc, hand-crafted strategies applied to raw…
Open-Set Graph Anomaly Detection via Normal Structure Regularisation
Qizhou Wang, Guansong Pang, Mahsa Salehi +2
This paper considers an important Graph Anomaly Detection (GAD) task, namely open-set GAD, which aims to train a detection model using a small number of normal and anomaly nodes (r…
Cross-Domain Graph Anomaly Detection via Anomaly-aware Contrastive Alignment
Qizhou Wang, Guansong Pang, Mahsa Salehi +2
Cross-domain graph anomaly detection (CD-GAD) describes the problem of detecting anomalous nodes in an unlabelled target graph using auxiliary, related source graphs with labelled…