Research
Reliable Machine Learning, Uncertainty Quantification, Computer Vision
Interests
My research interest is machine learning, including trustworthy and robust machine learning, uncertainty of foundation models and interpretable machine learning. The main goal of my research is to quantify and mitigate the risk of machine learning systems so that the deployment of machine learning benefits each individual in our society.
Publications
Publications of specific relevance to the Centre for Multimodal AI
2026
Cost-Sensitive Conformal Training with Provably Controllable Learning BoundsJia X Shi Y Liu Z Xu Y Yan Y
Proceedings of the AAAI Conference on Artificial Intelligence. vol. 40 (27), 22274-22282.
14-03-2026 Adaptive momentum weight averaging reduces initialization noiseWan J Liu Z Gao J Wu X Chan AB
Pattern Recognition,
Elsevier vol. 171
01-03-2026 2025
RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented LearningZuo J Hu H Zhou Z Cui Y Liu Z Wang J Guan N Wang J et al.
2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). vol. 00, 17001-17007.
25-10-2025ConformalSAM: Unlocking the Potential of Foundational Segmentation Models in Semi-Supervised Semantic Segmentation with Conformal PredictionChen D Liu Z Yang C Wang D Yan Y Xu Y Ji X
International Conference on Computer Vision.
01-10-2025 Temporal Unlearnable Examples: Preventing Personal Video Data from Unauthorized Exploitation by Object TrackingWu Q Yu Y Kong C Liu Z Wan J Li H Kot A Chan A
International Conference on Computer Vision.
01-10-2025 Borrowing treasures from neighbors: In-context learning for multimodal learning with missing modalities and data scarcityZhi Z Liu Z Elbadawi M Daneshmend A Orlu M Basit A Demosthenous A Rodrigues M
Neurocomputing,
Elsevier vol. 647
01-09-2025 PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial AttacksFeng C Liu Z Zhi Z Bogunovic I Gerner-Beuerle C Rodrigues M
Proceedings of the AAAI Conference on Artificial Intelligence. vol. 39 (3), 2933-2941.
11-04-2025 AIM-Fair: Advancing Algorithmic Fairness via Selectively Fine-Tuning
Biased Models with Contextual Synthetic DataZhao Z Liu Z Cao Y Gong S Patras I
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Nashville, US 11 Jun 2025 - 16 Jun 2025.
07-03-2025 Wasserstein Modality Alignment Makes Your Multimodal Transformer More RobustZhi Z Sun Y Wu Q Liu Z Rodrigues M
Transactions on Machine Learning Research 23-01-2025 Get Confused Cautiously: Textual Sequence Memorization Erasure with Selective Entropy MaximizationZhang Z Liu Z Patras I
Proceedings International Conference on Computational Linguistics Coling., 10924-10939.
01-01-2025 QUERY-BASED KNOWLEDGE TRANSFER FOR HETEROGENEOUS LEARNING ENVIRONMENTSAlballa N Zhang W Liu Z Abdelmoniem AM Elhoseiny M Canini M
13th International Conference on Learning Representations Iclr 2025., 95820-95851.
01-01-2025 TFAR: A Training-Free Framework for Autonomous Reliable Reasoning in Visual Question AnsweringZhi Z Feng C Daneshmend A Orlu M Demosthenous A Yin L Li D Liu Z et al.
Transactions on Machine Learning Research vol. 2025-August
01-01-2025 2024
A Secure Image Watermarking Framework with Statistical Guarantees via Adversarial Attacks on Secret Key NetworksChen F Lin W Liu Z Chan AB
Lecture Notes in Computer Science. vol. 15098, 428-445.
10-11-2024 Get Confused Cautiously: Textual Sequence Memorization Erasure with Selective Entropy MaximizationZhang Z Liu Z Patras I
09-08-2024 2023
Variational Nested DropoutCui Y Mao Y Liu Z Li Q Chan AB Liu X Kuo T-W Xue CJ
IEEE Transactions on Pattern Analysis and Machine Intelligence,
Institute of Electrical and Electronics Engineers (IEEE) vol. 45 (8), 10519-10534.
30-06-2023 TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and GeneralizationLiu Z Xu Y Ji X Chan AB
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). vol. 00, 16436-16446.
24-06-2023 DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking TasksWu Q Yang T Liu Z Wu B Shan Y Chan AB
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). vol. 00, 14561-14571.
24-06-2023 Clustering Hidden Markov Models With Variational Bayesian Hierarchical EMLan H Liu Z Hsiao JH Yu D Chan AB
IEEE Transactions on Neural Networks and Learning Systems,
Institute of Electrical and Electronics Engineers (IEEE) vol. 34 (3), 1537-1551.
28-02-2023 Retrieval-Augmented Multiple Instance LearningCui Y Liu Z Chen Y Lu Y Yu X Liu X Kuo TW Rodrigues MRD et al.
Advances in Neural Information Processing Systems. vol. 36
01-01-2023 BAYES-MIL: A NEW PROBABILISTIC PERSPECTIVE ON ATTENTION-BASED MULTIPLE INSTANCE LEARNING FOR WHOLE SLIDE IMAGESCui Y Liu Z Liu X Liu X Wang C Kuo TW Xue CJ Chan AB
11th International Conference on Learning Representations Iclr 2023.
01-01-2023 2022
PRIMAL-GMM: PaRametrIc MAnifold Learning of Gaussian Mixture ModelsLiu Z Yu L Hsiao JH Chan AB
IEEE Transactions on Pattern Analysis and Machine Intelligence,
Institute of Electrical and Electronics Engineers (IEEE) vol. 44 (6), 3197-3211.
05-05-2022 Improved Fine-Tuning by Better Leveraging Pre-Training DataLiu Z Xu Y Xu Y Qian Q Li H Ji X Chan AB Jin R
Advances in Neural Information Processing Systems. vol. 35
01-01-2022 Boosting Adversarial Robustness From The Perspective of Effective Margin RegularizationLiu Z Chan AB
Bmvc 2022 33rd British Machine Vision Conference Proceedings.
01-01-2022 2021
Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive CompressionCui Y Liu Z Li Q Chan AB Xue CJ
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). vol. 00, 2392-2401.
25-06-2021 A Generalized Loss Function for Crowd Counting and LocalizationWan J Liu Z Chan AB
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). vol. 00, 1974-1983.
25-06-2021 2020
Fully nested neural network for adaptive compression and quantizationCui Y Liu Z Yao W Li Q Chan AB Kuo TW Xue CJ
Ijcai International Joint Conference on Artificial Intelligence. vol. 2021-January, 2080-2087.
01-01-2020 2019
Parametric Manifold Learning of Gaussian Mixture ModelsLiu Z Yu L Hsiao JH Chan AB
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence., 3073-3079.
01-08-2019 Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural DimensionsMasoud R Liu Z Ferianc M Treleaven P Rodrigues M
International Conference on Computational Linguistics.
SEBRA: Debiasing through Self-Guided Bias RankingKappiyath A Chaudhuri A Jaiswal AK Liu Z Li Y Zhu X Yin L
International Conference on Learning Representations.
The Pitfalls and Promise of Conformal Inference Under Adversarial AttacksLiu Z Cui Y Yan Y Xu Y Ji X Liu X Chan A
International Conference on Machine Learning Vienna, Austria 21 Jul 2024 - 27 Jul 2024.
