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Research
  1. Queen Mary University of London
  2. Research
  3. Publications

Publications: P Ziquan Liu

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Feng C, Liu Z, Zhi Z, Bogunovic I, Gerner-Beuerle C, Rodrigues M . PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attacks . Proceedings of the AAAI Conference on Artificial Intelligence . vol. 39 , 2933 - 2941 .
Zhao Z, Liu Z, Cao Y, Gong S, Patras I ( 2025 ) . AIM-Fair: Advancing Algorithmic Fairness via Selectively Fine-Tuning\n Biased Models with Contextual Synthetic Data .
Masoud RI, Liu Z, Ferianc M, Treleaven P, Rodrigues M ( 2025 ) . Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural Dimensions . Proceedings International Conference on Computational Linguistics Coling . vol. Part F206484-1 , 8474 - 8503 .
Zhang Z, Liu Z, Patras I ( 2025 ) . Get Confused Cautiously: Textual Sequence Memorization Erasure with Selective Entropy Maximization . COLING . 10924 - 10939 .
Kappiyath A, Chaudhuri A, Jaiswal A, Liu Z, Li Y, Zhu X, Yin L ( 2025 ) . SEBRA: DEBIASING THROUGH SELF-GUIDED BIAS RANKING . 13th International Conference on Learning Representations Iclr 2025 . 59868 - 59890 .
Zhi Z, Sun Y, Wu Q, Liu Z, Rodrigues M ( 2025 ) . Wasserstein Modality Alignment Makes Your Multimodal Transformer More Robust . Transactions on Machine Learning Research vol. 2025 ,
Chen F, Lin W, Liu Z, Chan AB ( 2025 ) . A Secure Image Watermarking Framework with Statistical Guarantees via Adversarial Attacks on Secret Key Networks . 428 - 445 .
Zhang Z, Liu Z, Patras I ( 2024 ) . Get Confused Cautiously: Textual Sequence Memorization Erasure with Selective Entropy Maximization . CoRR . vol. abs/2408.04983 ,
Liu Z, Cui Y, Yan Y, Xu Y, Ji X, Liu X, Chan AB ( 2024 ) . The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks . Proceedings of Machine Learning Research . vol. 235 , 30908 - 30928 .
Cui Y, Mao Y, Liu Z, Li Q, Chan AB, Liu X, Kuo T-W, Xue CJ ( 2023 ) . Variational Nested Dropout . IEEE Transactions on Pattern Analysis and Machine Intelligence vol. 45 , ( 8 ) 10519 - 10534 .
Wu Q, Yang T, Liu Z, Wu B, Shan Y, Chan AB ( 2023 ) . DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking Tasks . 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . Conference: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) from: 17/06/2023 to: 24/06/2023 ,
Liu Z, Xu Y, Ji X, Chan AB ( 2023 ) . TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization . 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . Conference: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) from: 17/06/2023 to: 24/06/2023 , 16436 - 16446 .
Lan H, Liu Z, Hsiao JH, Yu D, Chan AB ( 2023 ) . Clustering Hidden Markov Models With Variational Bayesian Hierarchical EM . IEEE Transactions on Neural Networks and Learning Systems vol. 34 , ( 3 ) 1537 - 1551 .
Cui Y, Liu Z, Liu X, Liu X, Wang C, Kuo TW, Xue CJ, Chan AB ( 2023 ) . BAYES-MIL: A NEW PROBABILISTIC PERSPECTIVE ON ATTENTION-BASED MULTIPLE INSTANCE LEARNING FOR WHOLE SLIDE IMAGES . 11th International Conference on Learning Representations Iclr 2023 .
Cui Y, Liu Z, Chen Y, Lu Y, Yu X, Liu X, Kuo TW, Rodrigues MRD et al. ( 2023 ) . Retrieval-Augmented Multiple Instance Learning . Advances in Neural Information Processing Systems . vol. 36 ,
Liu Z, Yu L, Hsiao JH, Chan AB ( 2022 ) . PRIMAL-GMM: PaRametrIc MAnifold Learning of Gaussian Mixture Models . IEEE Transactions on Pattern Analysis and Machine Intelligence vol. 44 , ( 6 ) 3197 - 3211 .
Liu Z, Chan AB ( 2022 ) . Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization . Bmvc 2022 33rd British Machine Vision Conference Proceedings .
Liu Z, Xu Y, Xu Y, Qian Q, Li H, Ji X, Chan AB, Jin R ( 2022 ) . Improved Fine-Tuning by Better Leveraging Pre-Training Data . Advances in Neural Information Processing Systems . vol. 35 ,
Wan J, Liu Z, Chan AB ( 2021 ) . A Generalized Loss Function for Crowd Counting and Localization . 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . Conference: 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) from: 20/06/2021 to: 25/06/2021 ,
Cui Y, Liu Z, Li Q, Chan AB, Xue CJ ( 2021 ) . Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression . 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . Conference: 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) from: 20/06/2021 to: 25/06/2021 , 2392 - 2401 .
Cui Y, Liu Z, Yao W, Li Q, Chan AB, Kuo TW, Xue CJ ( 2020 ) . Fully nested neural network for adaptive compression and quantization . Ijcai International Joint Conference on Artificial Intelligence . vol. 2021-January , 2080 - 2087 .
Liu Z, Yu L, Hsiao JH, Chan AB ( 2019 ) . Parametric Manifold Learning of Gaussian Mixture Models . Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence . Conference: Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19} from: 10/08/2019 to: 16/08/2019 , 3073 - 3079 .
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