Ziquan Liu

According to our database, Ziquan Liu authored at least 47 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Reinforcement Learning for Target Zone Blood Glucose Control.

David H. Mguni, Jing Dong, Wanrong Yang, Ziquan Liu, Muhammad Salman Haleem, Baoxiang Wang

CoRR, August, 2025

ConformalSAM: Unlocking the Potential of Foundational Segmentation Models in Semi-Supervised Semantic Segmentation with Conformal Prediction.

Danhui Chen, Ziquan Liu, Chuxi Yang, Dan Wang, Yan Yan, Yi Xu, Xiangyang Ji

CoRR, July, 2025

Temporal Unlearnable Examples: Preventing Personal Video Data from Unauthorized Exploitation by Object Tracking.

Qiangqiang Wu, Yi Yu, Chenqi Kong, Ziquan Liu, Jia Wan, Haoliang Li, Alex C. Kot, Antoni B. Chan

CoRR, July, 2025

V-STaR: Benchmarking Video-LLMs on Video Spatio-Temporal Reasoning.

Zixu Cheng, Jian Hu, Ziquan Liu, Chenyang Si, Wei Li, Shaogang Gong

CoRR, March, 2025

CASteer: Steering Diffusion Models for Controllable Generation.

Tatiana Gaintseva, Chengcheng Ma, Ziquan Liu, Martin Benning, Gregory G. Slabaugh, Jiankang Deng, Ismail Elezi

CoRR, March, 2025

Seeing and Reasoning with Confidence: Supercharging Multimodal LLMs with an Uncertainty-Aware Agentic Framework.

Zhuo Zhi, Chen Feng, Adam Daneshmend, Mine Orlu, Andreas Demosthenous, Lu Yin, Da Li, Ziquan Liu, Miguel R. D. Rodrigues

CoRR, March, 2025

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning.

Jiacheng Zuo, Haibo Hu, Zikang Zhou, Yufei Cui, Ziquan Liu, Jianping Wang, Nan Guan, Jin Wang, Chun Jason Xue

CoRR, January, 2025

Wasserstein Modality Alignment Makes Your Multimodal Transformer More Robust.

Zhuo Zhi, Yuxuan Sun, Qiangqiang Wu, Ziquan Liu, Miguel R. D. Rodrigues

Trans. Mach. Learn. Res., 2025

TFAR: A Training-Free Framework for Autonomous Reliable Reasoning in Visual Question Answering.

Zhuo Zhi, Chen Feng, Adam Daneshmend, Mine Orlu, Andreas Demosthenous, Lu Yin, Da Li, Ziquan Liu, Miguel R. D. Rodrigues

Trans. Mach. Learn. Res., 2025

Borrowing treasures from neighbors: In-context learning for multimodal learning with missing modalities and data scarcity.

Zhuo Zhi, Ziquan Liu, Moe Elbadawi, Adam Daneshmend, Mine Orlu, Abdul Basit, Andreas Demosthenous, Miguel R. D. Rodrigues

Neurocomputing, 2025

SEBRA : Debiasing through Self-Guided Bias Ranking.

Adarsh Kappiyath, Abhra Chaudhuri, Ajay Kumar Jaiswal, Ziquan Liu, Yunpeng Li, Xiatian Zhu, Lu Yin

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Query-based Knowledge Transfer for Heterogeneous Learning Environments.

Norah Alballa, Wenxuan Zhang, Ziquan Liu, Ahmed M. Abdelmoniem, Mohamed Elhoseiny, Marco Canini

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

AIM-Fair: Advancing Algorithmic Fairness via Selectively Fine-Tuning Biased Models with Contextual Synthetic Data.

Zengqun Zhao, Ziquan Liu, Yu Cao, Shaogang Gong, Ioannis Patras

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Get Confused Cautiously: Textual Sequence Memorization Erasure with Selective Entropy Maximization.

Zhaohan Zhang, Ziquan Liu, Ioannis Patras

Proceedings of the 31st International Conference on Computational Linguistics, 2025

Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural Dimensions.

Reem I. Masoud, Ziquan Liu, Martin Ferianc, Philip C. Treleaven, Miguel Rodrigues

Proceedings of the 31st International Conference on Computational Linguistics, 2025

PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attacks.

Chen Feng, Ziquan Liu, Zhuo Zhi, Ilija Bogunovic, Carsten Gerner-Beuerle, Miguel Rodrigues

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

A gender recognition method based on EEG microstates.

Yanxiang Niu, Xin Chen, Yuansen Chen, Zixuan Yao, Xuemei Chen, Ziquan Liu, Xiangyan Meng, Yanqing Liu, Zongya Zhao, Haojun Fan

Comput. Biol. Medicine, 2024

The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks.

Ziquan Liu, Yufei Cui, Yan Yan, Yi Xu, Xiangyang Ji, Xue Liu, Antoni B. Chan

Proceedings of the Forty-first International Conference on Machine Learning, 2024

The Second Visual Object Tracking Segmentation VOTS2024 Challenge Results.

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

Proceedings of the Computer Vision - ECCV 2024 Workshops, 2024

A Secure Image Watermarking Framework with Statistical Guarantees via Adversarial Attacks on Secret Key Networks.

Feiyu Chen, Wei Lin, Ziquan Liu, Antoni B. Chan

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Analysing educational scientific collaboration through multilayer networks: patterns, impact and network generation model.

Shenwen Chen, Yisen Wang, Ziquan Liu, Wenbo Du, Lei Zheng, Runran Liu

J. Complex Networks, September, 2023

Variational Nested Dropout.

Yufei Cui, Yu Mao, Ziquan Liu, Qiao Li, Antoni B. Chan, Xue (Steve) Liu, Tei-Wei Kuo, Chun Jason Xue

IEEE Trans. Pattern Anal. Mach. Intell., August, 2023

Clustering Hidden Markov Models With Variational Bayesian Hierarchical EM.

Hui Lan, Ziquan Liu, Janet H. Hsiao, Dan Yu, Antoni B. Chan

IEEE Trans. Neural Networks Learn. Syst., March, 2023

Retrieval-Augmented Multiple Instance Learning.

Yufei Cui, Ziquan Liu, Yixin Chen, Yuchen Lu, Xinyue Yu, Xue (Steve) Liu, Tei-Wei Kuo, Miguel Rodrigues, Chun Jason Xue, Antoni B. Chan

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Bayes-MIL: A New Probabilistic Perspective on Attention-based Multiple Instance Learning for Whole Slide Images.

Yufei Cui, Ziquan Liu, Xiangyu Liu, Xue Liu, Cong Wang, Tei-Wei Kuo, Chun Jason Xue, Antoni B. Chan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking Tasks.

Qiangqiang Wu, Tianyu Yang, Ziquan Liu, Baoyuan Wu, Ying Shan, Antoni B. Chan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization.

Ziquan Liu, Yi Xu, Xiangyang Ji, Antoni B. Chan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

PRIMAL-GMM: PaRametrIc MAnifold Learning of Gaussian Mixture Models.

Ziquan Liu, Lei Yu, Janet H. Hsiao, Antoni B. Chan

IEEE Trans. Pattern Anal. Mach. Intell., 2022

An Empirical Study on Distribution Shift Robustness From the Perspective of Pre-Training and Data Augmentation.

Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Rong Jin, Xiangyang Ji, Antoni B. Chan

CoRR, 2022

Improved Fine-Tuning by Better Leveraging Pre-Training Data.

Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Xiangyang Ji, Antoni B. Chan, Rong Jin

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization.

Ziquan Liu, Antoni B. Chan

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021

Clustering Hidden Markov Models with Variational Bayesian Hierarchical EM.

Hui Lan, Ziquan Liu, Janet H. Hsiao, Dan Yu, Antoni B. Chan

Dataset, January, 2021

Improved Fine-tuning by Leveraging Pre-training Data: Theory and Practice.

Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Antoni B. Chan, Rong Jin

CoRR, 2021

The Implicit Biases of Stochastic Gradient Descent on Deep Neural Networks with Batch Normalization.

Ziquan Liu, Yufei Cui, Jia Wan, Yu Mao, Antoni B. Chan

CoRR, 2021

Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression.

Yufei Cui, Ziquan Liu, Qiao Li, Yu Mao, Antoni B. Chan, Chun Jason Xue

CoRR, 2021

Maintenance Decision Generator for Electrical Equipment Based on Reinforcement Learning.

Ruifan Li, Zeyuan Wang, Yifan Du, Zepeng Zhai, Yongping Xiong, Ziquan Liu

Proceedings of the SPML 2021: 4th International Conference on Signal Processing and Machine Learning, Beijing, China, August 18, 2021

A Deep Image Denoising Method at Transmit Electricity Surveillance Environment.

Nan Yao, Ziquan Liu, Zhen Wang, Yongling Lu, Jianhua Qin

Proceedings of the 2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, 2021

Target Detection of Engineering Vehicles Based on Co-learning Labels.

Zhen Wang, Nan Yao, Ziquan Liu, Xueqiong Zhu, Hai Xue

Proceedings of the 2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, 2021

Bolt Defect Detection Based on CenterNet Model.

Nan Yao, Yuxi Zhao, Xi Wu, Ziquan Liu, Jianhua Qin

Proceedings of the IEEE Intl Conf on Dependable, 2021

Detection of Transmission Line Corridors Risk Intrusion based on B-CNN.

Nan Yao, Ziquan Liu, Zhen Wang, Yongling Lu, Hai Xue

Proceedings of the IEEE Intl Conf on Dependable, 2021

Feature Pyramid Hierarchy based DeltaNet Network for Insulator Defect Detection.

Ziquan Liu, Nan Yao, Xi Wu, Jinggang Yang, Hai Xue

Proceedings of the IEEE Intl Conf on Dependable, 2021

A Generalized Loss Function for Crowd Counting and Localization.

Jia Wan, Ziquan Liu, Antoni B. Chan

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression.

Yufei Cui, Ziquan Liu, Qiao Li, Antoni B. Chan, Chun Jason Xue

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Improve Generalization and Robustness of Neural Networks via Weight Scale Shifting Invariant Regularizations.

Ziquan Liu, Yufei Cui, Antoni B. Chan

CoRR, 2020

Fully Nested Neural Network for Adaptive Compression and Quantization.

Yufei Cui, Ziquan Liu, Wuguannan Yao, Qiao Li, Antoni B. Chan, Tei-Wei Kuo, Chun Jason Xue

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

Parametric Manifold Learning of Gaussian Mixture Models.

Ziquan Liu, Lei Yu, Janet H. Hsiao, Antoni B. Chan

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2017

Optimization of Spectrum-Energy Efficiency in Heterogeneous Communication Network.

Fangqing Gu, Ziquan Liu, Yiu-ming Cheung, Hai-Lin Liu

Proceedings of the Simulated Evolution and Learning - 11th International Conference, 2017