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2020 – today
- 2025
[j7]Zhuo Zhi, Ziquan Liu, Moe Elbadawi, Adam Daneshmend, Mine Orlu, Abdul Basit, Andreas Demosthenous, Miguel R. D. Rodrigues:
Borrowing treasures from neighbors: In-context learning for multimodal learning with missing modalities and data scarcity. Neurocomputing 647: 130502 (2025)- [j6]Zhuo Zhi, Yuxuan Sun, Qiangqiang Wu, Ziquan Liu, Miguel R. D. Rodrigues:
Wasserstein Modality Alignment Makes Your Multimodal Transformer More Robust. Trans. Mach. Learn. Res. 2025 (2025) - [c25]Chen Feng, Ziquan Liu, Zhuo Zhi, Ilija Bogunovic, Carsten Gerner-Beuerle, Miguel Rodrigues:
PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attacks. AAAI 2025: 2933-2941 - [c24]Reem I. Masoud, Ziquan Liu, Martin Ferianc, Philip C. Treleaven, Miguel Rodrigues:
Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural Dimensions. COLING 2025: 8474-8503 - [c23]Zhaohan Zhang, Ziquan Liu, Ioannis Patras:
Get Confused Cautiously: Textual Sequence Memorization Erasure with Selective Entropy Maximization. COLING 2025: 10924-10939 - [c22]Norah Alballa, Wenxuan Zhang, Ziquan Liu, Ahmed M. Abdelmoniem, Mohamed Elhoseiny, Marco Canini:
Query-based Knowledge Transfer for Heterogeneous Learning Environments. ICLR 2025 - [c21]Adarsh Kappiyath, Abhra Chaudhuri, Ajay Kumar Jaiswal, Ziquan Liu, Yunpeng Li, Xiatian Zhu, Lu Yin:
SEBRA : Debiasing through Self-Guided Bias Ranking. ICLR 2025 - [i20]Jiacheng Zuo, Haibo Hu, Zikang Zhou, Yufei Cui, Ziquan Liu, Jianping Wang, Nan Guan, Jin Wang, Chun Jason Xue:
RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning. CoRR abs/2501.12296 (2025) - [i19]Adarsh Kappiyath, Abhra Chaudhuri, Ajay Jaiswal, Ziquan Liu, Yunpeng Li, Xiatian Zhu, Lu Yin:
Sebra: Debiasing Through Self-Guided Bias Ranking. CoRR abs/2501.18277 (2025) - [i18]Zengqun Zhao, Ziquan Liu, Yu Cao, Shaogang Gong, Ioannis Patras:
AIM-Fair: Advancing Algorithmic Fairness via Selectively Fine-Tuning Biased Models with Contextual Synthetic Data. CoRR abs/2503.05665 (2025) - [i17]Zhuo Zhi, Chen Feng, Adam Daneshmend, Mine Orlu, Andreas Demosthenous, Lu Yin, Da Li, Ziquan Liu, Miguel R. D. Rodrigues:
Seeing and Reasoning with Confidence: Supercharging Multimodal LLMs with an Uncertainty-Aware Agentic Framework. CoRR abs/2503.08308 (2025) - [i16]Tatiana Gaintseva, Chengcheng Ma, Ziquan Liu, Martin Benning, Gregory G. Slabaugh, Jiankang Deng, Ismail Elezi:
CASteer: Steering Diffusion Models for Controllable Generation. CoRR abs/2503.09630 (2025) - [i15]Zixu Cheng, Jian Hu, Ziquan Liu, Chenyang Si, Wei Li, Shaogang Gong:
V-STaR: Benchmarking Video-LLMs on Video Spatio-Temporal Reasoning. CoRR abs/2503.11495 (2025) - [i14]Norah Alballa, Wenxuan Zhang, Ziquan Liu, Ahmed M. Abdelmoniem, Mohamed Elhoseiny, Marco Canini:
Query-based Knowledge Transfer for Heterogeneous Learning Environments. CoRR abs/2504.09205 (2025) - 2024
- [j5]Yanxiang Niu, Xin Chen, Yuansen Chen, Zixuan Yao, Xuemei Chen, Ziquan Liu, Xiangyan Meng, Yanqing Liu, Zongya Zhao, Haojun Fan:
A gender recognition method based on EEG microstates. Comput. Biol. Medicine 173: 108366 (2024) - [c20]Matej Kristan, Jirí Matas, Pavel Tokmakov, Michael Felsberg, Luka Cehovin Zajc, Alan Lukezic, Khanh-Tung Tran, Xuan-Son Vu, Johanna Björklund, Hyung Jin Chang, Gustavo Fernández, Minasadat Attari, Antoni B. Chan, Liang Chen, Xin Chen, Jaired Collins, Yutao Cui, Ganesh Sai Manas Devarapu, Yinglong Du, Heng Fan, Wan-Cyuan Fan, Zhenhua Feng, Mingqi Gao, Rama Krishna Gorthi, Raghav Goyal, Jungong Han, Bijaya Kumar Hatuwal, Zhenyu He, Xiantao Hu, Xingsen Huang, Yuqing Huang, Dongmei Jiang, Ben Kang, Kannappan Palaniappan, Josef Kittler, Simiao Lai, Ning Li, Xiaohai Li, Xin Li, Cheng Liang, Liting Lin, Haibin Ling, Ting Liu, Ziquan Liu, Huchuan Lu, Yifei Luo, Deshui Miao, Juan Mogollon, Ziqi Pang, Jaswanth Reddy Pochimireddy, Viktor Prutyanov, Gani Rahmon, Aleksandr Romanov
, Liangtao Shi, Mennatullah Siam, Leonid Sigal, Arun Kumar Sivapuram, Roman A. Solovyev, Elham Soltani Kazemi, Imad Eddine Toubal, Jia Wan, Limin Wang, Xinying Wang, Yaowei Wang, Yu-Xiong Wang, Zhiquan Wang, Gangshan Wu, Qiangqiang Wu, Xiaojun Wu, Zihao Xia, Jinxia Xie, Chenlong Xu, Tianyang Xu, Yong Xu, Chaocan Xue, Chao Yang, Jinyu Yang, Ming-Hsuan Yang, Chenyang Yu, Ke Yu, Chunhui Zhang, Jiaming Zhang, Zhipeng Zhang, Feng Zheng, Yaozong Zheng, Bineng Zhong, Jinglin Zhou, Junbao Zhou, Yong Zhou, Zikun Zhou, Guibo Zhu, Jiawen Zhu, Xuefeng Zhu, Vladimir V. Zunin:
The Second Visual Object Tracking Segmentation VOTS2024 Challenge Results. ECCV Workshops (7) 2024: 357-383 - [c19]Feiyu Chen, Wei Lin, Ziquan Liu, Antoni B. Chan:
A Secure Image Watermarking Framework with Statistical Guarantees via Adversarial Attacks on Secret Key Networks. ECCV (40) 2024: 428-445 - [c18]Ziquan Liu, Yufei Cui, Yan Yan, Yi Xu, Xiangyang Ji, Xue Liu, Antoni B. Chan:
The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks. ICML 2024 - [i13]Chen Feng, Ziquan Liu, Zhuo Zhi, Ilija Bogunovic, Carsten Gerner-Beuerle, Miguel Rodrigues:
PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attacks. CoRR abs/2402.02629 (2024) - [i12]Zhuo Zhi, Ziquan Liu, Moe Elbadawi, Adam Daneshmend, Mine Orlu, Abdul Basit, Andreas Demosthenous, Miguel Rodrigues:
Borrowing Treasures from Neighbors: In-Context Learning for Multimodal Learning with Missing Modalities and Data Scarcity. CoRR abs/2403.09428 (2024) - [i11]Ziquan Liu, Yufei Cui, Yan Yan, Yi Xu, Xiangyang Ji, Xue Liu, Antoni B. Chan:
The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks. CoRR abs/2405.08886 (2024) - [i10]Zhaohan Zhang, Ziquan Liu, Ioannis Patras:
Get Confused Cautiously: Textual Sequence Memorization Erasure with Selective Entropy Maximization. CoRR abs/2408.04983 (2024) - 2023
- [j4]Shenwen Chen, Yisen Wang, Ziquan Liu, Wenbo Du, Lei Zheng, Runran Liu:
Analysing educational scientific collaboration through multilayer networks: patterns, impact and network generation model. J. Complex Networks 11(5) (2023) - [j3]Yufei Cui, Yu Mao, Ziquan Liu, Qiao Li, Antoni B. Chan, Xue (Steve) Liu, Tei-Wei Kuo, Chun Jason Xue:
Variational Nested Dropout. IEEE Trans. Pattern Anal. Mach. Intell. 45(8): 10519-10534 (2023) - [j2]Hui Lan, Ziquan Liu, Janet H. Hsiao, Dan Yu, Antoni B. Chan:
Clustering Hidden Markov Models With Variational Bayesian Hierarchical EM. IEEE Trans. Neural Networks Learn. Syst. 34(3): 1537-1551 (2023) - [c17]Qiangqiang Wu, Tianyu Yang, Ziquan Liu, Baoyuan Wu, Ying Shan, Antoni B. Chan:
DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking Tasks. CVPR 2023: 14561-14571 - [c16]Ziquan Liu, Yi Xu, Xiangyang Ji, Antoni B. Chan:
TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization. CVPR 2023: 16436-16446 - [c15]Yufei Cui, Ziquan Liu, Xiangyu Liu, Xue Liu, Cong Wang, Tei-Wei Kuo, Chun Jason Xue, Antoni B. Chan:
Bayes-MIL: A New Probabilistic Perspective on Attention-based Multiple Instance Learning for Whole Slide Images. ICLR 2023 - [c14]Yufei Cui, Ziquan Liu, Yixin Chen, Yuchen Lu, Xinyue Yu, Xue (Steve) Liu, Tei-Wei Kuo, Miguel Rodrigues, Chun Jason Xue, Antoni B. Chan:
Retrieval-Augmented Multiple Instance Learning. NeurIPS 2023 - [i9]Ziquan Liu, Yi Xu, Xiangyang Ji, Antoni B. Chan:
TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization. CoRR abs/2303.11135 (2023) - [i8]Qiangqiang Wu, Tianyu Yang, Ziquan Liu, Baoyuan Wu, Ying Shan, Antoni B. Chan:
DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking Tasks. CoRR abs/2304.00571 (2023) - [i7]Reem I. Masoud, Ziquan Liu, Martin Ferianc, Philip C. Treleaven, Miguel Rodrigues:
Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural Dimensions. CoRR abs/2309.12342 (2023) - 2022
- [j1]Ziquan Liu, Lei Yu, Janet H. Hsiao, Antoni B. Chan:
PRIMAL-GMM: PaRametrIc MAnifold Learning of Gaussian Mixture Models. IEEE Trans. Pattern Anal. Mach. Intell. 44(6): 3197-3211 (2022) - [c13]Ziquan Liu, Antoni B. Chan:
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization. BMVC 2022: 367 - [c12]Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Xiangyang Ji, Antoni B. Chan, Rong Jin:
Improved Fine-Tuning by Better Leveraging Pre-Training Data. NeurIPS 2022 - [i6]Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Rong Jin, Xiangyang Ji, Antoni B. Chan:
An Empirical Study on Distribution Shift Robustness From the Perspective of Pre-Training and Data Augmentation. CoRR abs/2205.12753 (2022) - [i5]Ziquan Liu, Antoni B. Chan:
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization. CoRR abs/2210.05118 (2022) - 2021
- [c11]Jia Wan, Ziquan Liu, Antoni B. Chan:
A Generalized Loss Function for Crowd Counting and Localization. CVPR 2021: 1974-1983 - [c10]Yufei Cui, Ziquan Liu, Qiao Li, Antoni B. Chan, Chun Jason Xue:
Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression. CVPR 2021: 2392-2401 - [c9]Nan Yao, Yuxi Zhao, Xi Wu, Ziquan Liu, Jianhua Qin:
Bolt Defect Detection Based on CenterNet Model. DASC/PiCom/CBDCom/CyberSciTech 2021: 731-737 - [c8]Nan Yao, Ziquan Liu, Zhen Wang, Yongling Lu, Hai Xue:
Detection of Transmission Line Corridors Risk Intrusion based on B-CNN. DASC/PiCom/CBDCom/CyberSciTech 2021: 738-744 - [c7]Ziquan Liu, Nan Yao, Xi Wu, Jinggang Yang, Hai Xue:
Feature Pyramid Hierarchy based DeltaNet Network for Insulator Defect Detection. DASC/PiCom/CBDCom/CyberSciTech 2021: 745-750 - [c6]Nan Yao, Ziquan Liu, Zhen Wang, Yongling Lu, Jianhua Qin:
A Deep Image Denoising Method at Transmit Electricity Surveillance Environment. HPCC/DSS/SmartCity/DependSys 2021: 1676-1684 - [c5]Zhen Wang, Nan Yao, Ziquan Liu, Xueqiong Zhu, Hai Xue:
Target Detection of Engineering Vehicles Based on Co-learning Labels. HPCC/DSS/SmartCity/DependSys 2021: 1693-1698 - [c4]Ruifan Li, Zeyuan Wang, Yifan Du, Zepeng Zhai, Yongping Xiong, Ziquan Liu:
Maintenance Decision Generator for Electrical Equipment Based on Reinforcement Learning. SPML 2021: 160-165 - [d1]Hui Lan, Ziquan Liu, Janet H. Hsiao, Dan Yu, Antoni B. Chan:
Clustering Hidden Markov Models with Variational Bayesian Hierarchical EM. Zenodo, 2021
- [i4]Yufei Cui, Ziquan Liu, Qiao Li, Yu Mao, Antoni B. Chan, Chun Jason Xue:
Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression. CoRR abs/2101.11353 (2021) - [i3]Ziquan Liu, Yufei Cui, Jia Wan, Yu Mao, Antoni B. Chan:
The Implicit Biases of Stochastic Gradient Descent on Deep Neural Networks with Batch Normalization. CoRR abs/2102.03497 (2021) - [i2]Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Antoni B. Chan, Rong Jin:
Improved Fine-tuning by Leveraging Pre-training Data: Theory and Practice. CoRR abs/2111.12292 (2021) - 2020
- [c3]Yufei Cui, Ziquan Liu, Wuguannan Yao, Qiao Li, Antoni B. Chan, Tei-Wei Kuo, Chun Jason Xue:
Fully Nested Neural Network for Adaptive Compression and Quantization. IJCAI 2020: 2080-2087 - [i1]Ziquan Liu, Yufei Cui, Antoni B. Chan:
Improve Generalization and Robustness of Neural Networks via Weight Scale Shifting Invariant Regularizations. CoRR abs/2008.02965 (2020)
2010 – 2019
- 2019
- [c2]Ziquan Liu, Lei Yu, Janet H. Hsiao, Antoni B. Chan:
Parametric Manifold Learning of Gaussian Mixture Models. IJCAI 2019: 3073-3079 - 2017
- [c1]Fangqing Gu, Ziquan Liu, Yiu-ming Cheung, Hai-Lin Liu:
Optimization of Spectrum-Energy Efficiency in Heterogeneous Communication Network. SEAL 2017: 821-832
Coauthor Index
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