2024
Cross-center Model Adaptive Tooth Segmentation.
Ruizhe Chen, Jianfei Yang, Huimin Xiong, Ruiling Xu, Yang Feng, Jian Wu, and Zuozhu Liu*.
Medical Image Analysis, 2024.
Ruizhe Chen, Jianfei Yang, Huimin Xiong, Ruiling Xu, Yang Feng, Jian Wu, and Zuozhu Liu*.
Medical Image Analysis, 2024.
MedCoT: Medical Chain of Thought via Hierarchical Expert.
Jiaxiang Liu, Yuan Wang, Jiawei Du, Joey Tianyi Zhou and Zuozhu Liu*.
EMNLP, 2024.
Jiaxiang Liu, Yuan Wang, Jiawei Du, Joey Tianyi Zhou and Zuozhu Liu*.
EMNLP, 2024.
Ladder: A Model-Agnostic Framework Boosting LLM-based Machine Translation to the Next Level.
Zhaopeng Feng, Ruizhe Chen, Yan Zhang, Zijie Meng and Zuozhu Liu*.
EMNLP, 2024.
Zhaopeng Feng, Ruizhe Chen, Yan Zhang, Zijie Meng and Zuozhu Liu*.
EMNLP, 2024.
BiasAlert: A Plug-and-play Tool for Social Bias Detection in LLMs.
Zhiting Fan, Ruizhe Chen, Ruiling Xu and Zuozhu Liu*.
EMNLP, 2024.
Zhiting Fan, Ruizhe Chen, Ruiling Xu and Zuozhu Liu*.
EMNLP, 2024.
VPL: Visual Proxy Learning Framework for Zero-Shot Medical Image Diagnosis.
Jiaxiang Liu, Tianxiang Hu, Huimin Xiong, Jiawei Du, Yang Feng, Jian Wu, Joey Zhou, Zuozhu Liu*.
Findings of EMNLP, 2024.
Jiaxiang Liu, Tianxiang Hu, Huimin Xiong, Jiawei Du, Yang Feng, Jian Wu, Joey Zhou, Zuozhu Liu*.
Findings of EMNLP, 2024.
Med-MoE: Mixture of Domain-Specific Experts for Lightweight Medical Vision-Language Models.
Songtao Jiang, Tuo Zheng, Yan Zhang, Yeying Jin, Li Yuan, Zuozhu Liu*.
Findings of EMNLP, 2024.
Songtao Jiang, Tuo Zheng, Yan Zhang, Yeying Jin, Li Yuan, Zuozhu Liu*.
Findings of EMNLP, 2024.
LETA: Tooth Alignment Prediction Based on Dual-branch Latent Encoding.
Z. Shi, Z. Meng, R. Chen, Y. Feng, Z. Zhao, J. Hao, B. Fang, Zuozhu Liu* and Y. Zhen*.
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2024.
Z. Shi, Z. Meng, R. Chen, Y. Feng, Z. Zhao, J. Hao, B. Fang, Zuozhu Liu* and Y. Zhen*.
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2024.
Comprehensive assessment of mRNA isoform detection methods for long-read sequencing data.
Y. Su, Z. Yu, S. Jin, Z. Ai, R. Yuan, X. Chen, Z. Xue, Y. Guo, D. Chen, H. Liang, Zuozhu Liu and Wanlu Liu.
Nature Communications, Vol.15 No.1, 2024.
Y. Su, Z. Yu, S. Jin, Z. Ai, R. Yuan, X. Chen, Z. Xue, Y. Guo, D. Chen, H. Liang, Zuozhu Liu and Wanlu Liu.
Nature Communications, Vol.15 No.1, 2024.
FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data.
Z. Xiao#, Z. Chen#, L. Liu, Y. Feng, J.T. Zhou, J. Wu, W. Liu, H.H. Yang and Zuozhu Liu*.
ICLR 2024.
Z. Xiao#, Z. Chen#, L. Liu, Y. Feng, J.T. Zhou, J. Wu, W. Liu, H.H. Yang and Zuozhu Liu*.
ICLR 2024.
Learnable Privacy Neurons Localization in Language Models.
R.Chen, T. Hu, Y. Feng and Zuozhu Liu*.
ACL 2024.
R.Chen, T. Hu, Y. Feng and Zuozhu Liu*.
ACL 2024.
PX2Tooth: Reconstructing the 3D Point Cloud Teeth from a Single Panoramic X-ray.
W. Ma, H. Wu, Z. Xiao, Y. Feng, J. Wu and Zuozhu Liu*.
MICCAI 2024.
W. Ma, H. Wu, Z. Xiao, Y. Feng, J. Wu and Zuozhu Liu*.
MICCAI 2024.
Deep learning-enabled 3D multimodal fusion of cone-beam CT and intraoral mesh scans for clinically applicable tooth-bone reconstruction.
J. Liu, J. Hao, H. Lin, W. Pan, J. Yang, Y. Feng, G. Wang, J. Li, Z. Jin, Z. Zhao & Zuozhu Liu*.
Patterns, Cell Press, Vol.4 No.9, 100825, 2023.
J. Liu, J. Hao, H. Lin, W. Pan, J. Yang, Y. Feng, G. Wang, J. Li, Z. Jin, Z. Zhao & Zuozhu Liu*.
Patterns, Cell Press, Vol.4 No.9, 100825, 2023.
2023
Empirical Study of Zero-shot NER with ChatGPT.
T. Xie, Q. Li, J. Zhang, Y. Zhang, Zuozhu Liu, H. Wang.
EMNLP 2023.
T. Xie, Q. Li, J. Zhang, Y. Zhang, Zuozhu Liu, H. Wang.
EMNLP 2023.
How Well Do Text Embedding Models Understand Syntax?
Y. Zhang, Z. Feng, Z. Teng, Zuozhu Liu*, H. Li.
EMNLP 2023.
Y. Zhang, Z. Feng, Z. Teng, Zuozhu Liu*, H. Li.
EMNLP 2023.
Towards Distribution-Agnostic Generalized Category Discovery.
J. Bai, Zuozhu Liu*, H. Wang, R. Chen, L. Mu, X. Li, J. T. Zhou, Y. Feng, J. Wu, H. Hu.
NeurIPS 2023.
J. Bai, Zuozhu Liu*, H. Wang, R. Chen, L. Mu, X. Li, J. T. Zhou, Y. Feng, J. Wu, H. Hu.
NeurIPS 2023.
Fast Model Debias with Machine Unlearning.
R. Chen, J. Yang, H. Xiong, J. Bai, T. Hu, J. Hao, Y. Feng, J. T.i Zhou, J. Wu, Zuozhu Liu*.
NeurIPS 2023.
R. Chen, J. Yang, H. Xiong, J. Bai, T. Hu, J. Hao, Y. Feng, J. T.i Zhou, J. Wu, Zuozhu Liu*.
NeurIPS 2023.
Fed-GraB: Federated Long-tailed Learning with Self-Adjusting Gradient Balancer.
Z. Xiao, Z. Chen, S. Liu, J. Hao, H. Wang, Y. Feng, H. H. Yang, J. T. Zhou, J. Wu, Zuozhu Liu*.
NeurIPS 2023.
Z. Xiao, Z. Chen, S. Liu, J. Hao, H. Wang, Y. Feng, H. H. Yang, J. T. Zhou, J. Wu, Zuozhu Liu*.
NeurIPS 2023.
A Transformer-based Knowledge Distillation Network for Cortical Cataract Grading.
J. Wang, Z. Xu, W. Zheng, H. Ying, T. Chen, Z. Liu, D. Z. Chen, K. Yao and J. Wu.
IEEE Transactions on Medical Imaging, 2023.
J. Wang, Z. Xu, W. Zheng, H. Ying, T. Chen, Z. Liu, D. Z. Chen, K. Yao and J. Wu.
IEEE Transactions on Medical Imaging, 2023.
Parameter-Efficient Transfer Learning for Medical Visual Question Answering.
J. Liu, T. Hu, Y. Zhang, Y. Feng, J. Hao, J. Lv and Zuozhu Liu*.
IEEE Transactions on Emerging Topics in Computational Intelligence, 2023.
J. Liu, T. Hu, Y. Zhang, Y. Feng, J. Hao, J. Lv and Zuozhu Liu*.
IEEE Transactions on Emerging Topics in Computational Intelligence, 2023.
TSegFormer: 3D Tooth Segmentation in Intraoral Scans with Geometry Guided Transformer.
H. Xiong, K. Li, K. Tan, Y. Feng, J. T. Zhou, J. Hao, H. Ying, J. Wu, Zuozhu Liu*.
MICCAI 2023.
H. Xiong, K. Li, K. Tan, Y. Feng, J. T. Zhou, J. Hao, H. Ying, J. Wu, Zuozhu Liu*.
MICCAI 2023.
On the Effectiveness of Out-of-Distribution Data in Self-Supervised Long-Tail Learning.
Jianhong Bai#, Zuozhu Liu#, Hualiang Wang, Jin Hao, Yang Feng, Huanpeng Chu, Haoji Hu*.
ICLR 2023.
Jianhong Bai#, Zuozhu Liu#, Hualiang Wang, Jin Hao, Yang Feng, Huanpeng Chu, Haoji Hu*.
ICLR 2023.
Before
- Zuozhu Liu#, Xiaoxuan He#, Hualiang Wang, Huimin Xiong, Yan Zhang, Gaoang Wang, Jin Hao, Yang Feng, Fudong Zhu, Haoji Hu*. “Hierarchical Self-supervised Learning for 3D Tooth Segmentation in Intra-oral Mesh Scans.” IEEE Transactions on Medical Imaging, 2022.
- Yiming Chen, Yan Zhang, Bin Wang, Zuozhu Liu*, Haizhou Li. “Generate, Discriminate and Contrast: A Semi-Supervised Sentence Representation Learning Framework.” EMNLP, 2022.
- Hualiang Wang, Siming Fu, Xiaoxuan He, Hangxiang Fang, Zuozhu Liu, Haoji Hu*. “Towards Calibrated Hyper-Sphere Representation via Distribution Overlap Coefficient for Long-tailed Learning”, ECCV (Oral), 2022.
- Zihan Chen#, Songshang Liu#, Howard. H. Yang, Zuozhu Liu*. “Towards Federated Long-tailed Learning”, FL-IJCAI, 2022.
- Hualiang Wang, Huanpeng Chu, Siming Fu, Zuozhu Liu, Haoji Hu*. “Renovate Yourself: Calibrating Feature Representation of Misclassified Pixels for Semantic Segmentation“, AAAI 2022.
- Lize Wu#, Ziwei Xue#, Siqian Jin, Jinchun Zhang, Yadan Bai, Xuexiao Jin, Chaochen Wang, Lie Wang, Zuozhu Liu, James Wang, Linrong Lu*, Wanlu Liu*. “huARdb: human Antigen Receptor database for interactive clonotype-transcriptome analysis at the single-cell level”, Nucleic Acids Research, 2021.
- G. Wang, R. Gu, Zuozhu Liu, W. Hu, M. Song, J.-N. Hwang, “Track without Appearance: Learn Box and Tracklet Embedding with Local and Global Motion Patterns for Vehicle Tracking”, ICCV, 2021.
- Jin Hao, Wen Liao, Yueling Zhang, Jerry Peng, Zoe Zhao, Zhang Chen, Bowen Zhou, Yang Feng, Zuozhu Liu*, Zhihe Zhao*. “Towards Clinically Applicable 3D Tooth Segmentation using Deep Learning”, Journal of Dental Research, 2021.
- Yan Zhang#, Ruidan He#, Zuozhu Liu*, Lidong Bing and Haizhou Li. “Bootstrapped Unsupervised Sentence Representation Learning”, ACL 2021.
- Yan Zhang#, Ruidan He#, Zuozhu Liu*, Kwan Hui Lim and Lidong Bing. “An Unsupervised Sentence Embedding Method by Mutual Information Maximization”, EMNLP 2020.
- Yan Zhang#, Zhijiang Guo#, Zhiyang Teng, Wei Lu, Shay B. Cohen, Zuozhu Liu and Lidong Bing. “Lightweight, Dynamic Graph Convolutional Networks for AMR-to-Text Generation”, EMNLP 2020.
- Zuozhu Liu, Thiparat Chotibut, Chris Hillar and Shaowei Lin. “Biologically Plausible Sequence Learning for Spiking Neural Network”, AAAI 2020.
- Howard Yang, Zuozhu Liu*, Tony Q.S. Quek, Vincent Poor. “Scheduling Policies for Federated Learning in Wireless Networks”, IEEE Transactions on Communications, 2019 （ESI Highly Cited Paper， IEEE Xplore Cover Paper）.
- Zuozhu Liu, Tony Q.S. Quek and Shaowei Lin. “Variational Probability Flow Learning for Biologically Plausible Training of Deep Neural Networks”, AAAI 2018.
- Zuozhu Liu, Wenyu Zhang, Tony Q.S. Quek and Shaowei Lin. “Deep Fusion of Heterogeneous Sensor Data”, ICASSP 2017 (Finalist of Best Student Paper).
- Zuozhu Liu, Wenyu Zhang, Shaowei Lin and Tony Q.S. Quek. “Heterogeneous Sensor Data Fusion by Deep Multimodal Encoding”, IEEE Journal of Selected Topics in Signal Processing, 2017.