Zuozhu Liu

According to our database, Zuozhu Liu authored at least 52 papers between 2015 and 2024.

Collaborative distances:

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

2024

DIVOTrack: A Novel Dataset and Baseline Method for Cross-View Multi-Object Tracking in DIVerse Open Scenes.

Shengyu Hao, Peiyuan Liu, Yibing Zhan, Kaixun Jin, Zuozhu Liu, Mingli Song, Jenq-Neng Hwang, Gaoang Wang

Int. J. Comput. Vis., April, 2024

A Transformer-Based Knowledge Distillation Network for Cortical Cataract Grading.

Jinhong Wang, Zhe Xu, Wenhao Zheng, Haochao Ying, Tingting Chen, Zuozhu Liu, Danny Z. Chen, Ke Yao, Jian Wu

IEEE Trans. Medical Imaging, March, 2024

Knowledge-guided pre-training and fine-tuning: Video representation learning for action recognition.

Guanhong Wang, Yang Zhou, Zhanhao He, Keyu Lu, Yang Feng, Zuozhu Liu, Gaoang Wang

Neurocomputing, February, 2024

Improving LLM-based Machine Translation with Systematic Self-Correction.

Zhaopeng Feng, Yan Zhang, Hao Li, Wenqiang Liu, Jun Lang, Yang Feng, Jian Wu, Zuozhu Liu

CoRR, 2024

UniEdit: A Unified Tuning-Free Framework for Video Motion and Appearance Editing.

Jianhong Bai, Tianyu He, Yuchi Wang, Junliang Guo, Haoji Hu, Zuozhu Liu, Jiang Bian

CoRR, 2024

FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data.

Zikai Xiao, Zihan Chen, Liyinglan Liu, Yang Feng, Jian Wu, Wanlu Liu, Joey Tianyi Zhou, Howard Hao Yang, Zuozhu Liu

CoRR, 2024

Divide and Conquer for Large Language Models Reasoning.

Zijie Meng, Yan Zhang, Zhaopeng Feng, Yang Feng, Gaoang Wang, Joey Tianyi Zhou, Jian Wu, Zuozhu Liu

CoRR, 2024

Robustness-Guided Image Synthesis for Data-Free Quantization.

Jianhong Bai, Yuchen Yang, Huanpeng Chu, Hualiang Wang, Zuozhu Liu, Ruizhe Chen, Xiaoxuan He, Lianrui Mu, Chengfei Cai, Haoji Hu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Deep learning-enabled 3D multimodal fusion of cone-beam CT and intraoral mesh scans for clinically applicable tooth-bone reconstruction.

Jiaxiang Liu, Jin Hao, Hangzheng Lin, Wei Pan, Jianfei Yang, Yang Feng, Gaoang Wang, Jin Li, Zuolin Jin, Zhihe Zhao, Zuozhu Liu

Patterns, September, 2023

Hierarchical Self-Supervised Learning for 3D Tooth Segmentation in Intra-Oral Mesh Scans.

Zuozhu Liu, Xiaoxuan He, Hualiang Wang, Huimin Xiong, Yan Zhang, Gaoang Wang, Jin Hao, Yang Feng, Fudong Zhu, Haoji Hu

IEEE Trans. Medical Imaging, February, 2023

A Fine-Grained Attention Model for High Accuracy Operational Robot Guidance.

Yinghao Chu, Daquan Feng, Zuozhu Liu, Lei Zhang, Zizhou Zhao, Zhenzhong Wang, Zhiyong Feng, Xiang-Gen Xia

IEEE Internet Things J., January, 2023

Self-Improving for Zero-Shot Named Entity Recognition with Large Language Models.

Tingyu Xie, Qi Li, Yan Zhang, Zuozhu Liu, Hongwei Wang

CoRR, 2023

Towards Distribution-Agnostic Generalized Category Discovery.

Jianhong Bai, Zuozhu Liu, Hualiang Wang, Ruizhe Chen, Lianrui Mu, Xiaomeng Li, Joey Tianyi Zhou, Yang Feng, Jian Wu, Haoji Hu

CoRR, 2023

A ChatGPT Aided Explainable Framework for Zero-Shot Medical Image Diagnosis.

Jiaxiang Liu, Tianxiang Hu, Yan Zhang, Xiaotang Gai, Yang Feng, Zuozhu Liu

CoRR, 2023

DIVOTrack: A Novel Dataset and Baseline Method for Cross-View Multi-Object Tracking in DIVerse Open Scenes.

Shenghao Hao, Peiyuan Liu, Yibing Zhan, Kaixun Jin, Zuozhu Liu, Mingli Song, Jenq-Neng Hwang, Gaoang Wang

CoRR, 2023

Fed-GraB: Federated Long-tailed Learning with Self-Adjusting Gradient Balancer.

Zikai Xiao, Zihan Chen, Songshang Liu, Hualiang Wang, Yang Feng, Jin Hao, Joey Tianyi Zhou, Jian Wu, Howard H. Yang, Zuozhu Liu

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

Fast Model DeBias with Machine Unlearning.

Ruizhe Chen, Jianfei Yang, Huimin Xiong, Jianhong Bai, Tianxiang Hu, Jin Hao, Yang Feng, Joey Tianyi Zhou, Jian Wu, Zuozhu Liu

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

Towards Distribution-Agnostic Generalized Category Discovery.

Jianhong Bai, Zuozhu Liu, Hualiang Wang, Ruizhe Chen, Lianrui Mu, Xiaomeng Li, Joey Tianyi Zhou, Yang Feng, Jian Wu, Haoji Hu

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

Model Adaptive Tooth Segmentation.

Ruizhe Chen, Jianfei Yang, Yang Feng, Jin Hao, Zuozhu Liu

Proceedings of the Medical Imaging with Deep Learning, 2023

TSegFormer: 3D Tooth Segmentation in Intraoral Scans with Geometry Guided Transformer.

Huimin Xiong, Kunle Li, Kaiyuan Tan, Yang Feng, Joey Tianyi Zhou, Jin Hao, Haochao Ying, Jian Wu, Zuozhu Liu

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Toothsegnet: Image Degradation Meets Tooth Segmentation in CBCT Images.

Jiaxiang Liu, Tianxiang Hu, Yang Feng, Wanghui Ding, Zuozhu Liu

Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 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

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Empirical Study of Zero-Shot NER with ChatGPT.

Tingyu Xie, Qi Li, Jian Zhang, Yan Zhang, Zuozhu Liu, Hongwei Wang

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

How Well Do Text Embedding Models Understand Syntax?

Yan Zhang, Zhaopeng Feng, Zhiyang Teng, Zuozhu Liu, Haizhou Li

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022

huARdb: human Antigen Receptor database for interactive clonotype-transcriptome analysis at the single-cell level.

Lize Wu, Ziwei Xue, Siqian Jin, Jinchun Zhang, Yixin Guo, Yadan Bai, Xuexiao Jin, Chaochen Wang, Lie Wang, Zuozhu Liu, James Q. Wang, Linrong Lu, Wanlu Liu

Nucleic Acids Res., 2022

Hybrid-Learning-Based Operational Visual Quality Inspection for Edge-Computing-Enabled IoT System.

Yinghao Chu, Daquan Feng, Zuozhu Liu, Zizhou Zhao, Zhenzhong Wang, Xiang-Gen Xia, Tony Q. S. Quek

IEEE Internet Things J., 2022

TFormer: 3D Tooth Segmentation in Mesh Scans with Geometry Guided Transformer.

Huimin Xiong, Kunle Li, Kaiyuan Tan, Yang Feng, Joey Tianyi Zhou, Jin Hao, Zuozhu Liu

CoRR, 2022

Towards Federated Long-Tailed Learning.

Zihan Chen, Songshang Liu, Hualiang Wang, Howard H. Yang, Tony Q. S. Quek, Zuozhu Liu

CoRR, 2022

AI-enabled Automatic Multimodal Fusion of Cone-Beam CT and Intraoral Scans for Intelligent 3D Tooth-Bone Reconstruction and Clinical Applications.

Jin Hao, Jiaxiang Liu, Jin Li, Wei Pan, Ruizhe Chen, Huimin Xiong, Kaiwei Sun, Hangzheng Lin, Wanlu Liu, Wanghui Ding, Jianfei Yang, Haoji Hu, Yueling Zhang, Yang Feng, Zeyu Zhao, Huikai Wu, Youyi Zheng, Bing Fang, Zuozhu Liu, Zhihe Zhao

CoRR, 2022

Unsupervised Pre-training Improves Tooth Segmentation in 3-Dimensional Intraoral Mesh Scans.

Xiaoxuan He, Hualiang Wang, Haoji Hu, Jianfei Yang, Yang Feng, Gaoang Wang, Zuozhu Liu

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

Modeling Freight-Sharing Platform Operations for Optimal Compensation Strategy Using Markov Decision Processes.

Siqi Shu, Zhengqi Chen, Zhe Yu, Shaosheng Cao, Guobin Wu, Donghai Shi, Gaoang Wang, Zuozhu Liu, Xiqun Chen, Xiaoxiang Na, Chao Wu, Simon Hu

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

Energy-Efficient Intelligent Pulmonary Auscultation for Post COVID-19 Era Wearable Monitoring Enabled by Two-Stage Hybrid Neural Network.

Bingqiang Liu, Ziyuan Wen, Hongling Zhu, Jinsheng Lai, Jiajun Wu, Heng Ping, Wenqing Liu, Guoyi Yu, Jianmin Zhang, Zuozhu Liu, Hesong Zeng, Chao Wang

Proceedings of the IEEE International Symposium on Circuits and Systems, 2022

Federated Stochastic Gradient Descent Begets Self-Induced Momentum.

Howard H. Yang, Zuozhu Liu, Yaru Fu, Tony Q. S. Quek, H. Vincent Poor

Proceedings of the IEEE International Conference on Acoustics, 2022

Generate, Discriminate and Contrast: A Semi-Supervised Sentence Representation Learning Framework.

Yiming Chen, Yan Zhang, Bin Wang, Zuozhu Liu, Haizhou Li

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Towards Calibrated Hyper-Sphere Representation via Distribution Overlap Coefficient for Long-Tailed Learning.

Hualiang Wang, Siming Fu, Xiaoxuan He, Hangxiang Fang, Zuozhu Liu, Haoji Hu

Proceedings of the Computer Vision, 2022

Tooth Defect Segmentation in 3D Mesh Scans Using Deep Learning.

Hao Chen, Yuhao Ge, Jiahao Wei, Huimin Xiong, Zuozhu Liu

Proceedings of the Artificial Intelligence - Second CAAI International Conference, 2022

Renovate Yourself: Calibrating Feature Representation of Misclassified Pixels for Semantic Segmentation.

Hualiang Wang, Huanpeng Chu, Siming Fu, Zuozhu Liu, Haoji Hu

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Track without Appearance: Learn Box and Tracklet Embedding with Local and Global Motion Patterns for Vehicle Tracking.

Gaoang Wang, Renshu Gu, Zuozhu Liu, Weijie Hu, Mingli Song, Jenq-Neng Hwang

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Bootstrapped Unsupervised Sentence Representation Learning.

Yan Zhang, Ruidan He, Zuozhu Liu, Lidong Bing, Haizhou Li

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

Scheduling Policies for Federated Learning in Wireless Networks.

Howard H. Yang, Zuozhu Liu, Tony Q. S. Quek, H. Vincent Poor

IEEE Trans. Commun., 2020

An Unsupervised Sentence Embedding Method byMutual Information Maximization.

Yan Zhang, Ruidan He, Zuozhu Liu, Kwan Hui Lim, Lidong Bing

CoRR, 2020

An Unsupervised Sentence Embedding Method by Mutual Information Maximization.

Yan Zhang, Ruidan He, Zuozhu Liu, Kwan Hui Lim, Lidong Bing

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Lightweight, Dynamic Graph Convolutional Networks for AMR-to-Text Generation.

Yan Zhang, Zhijiang Guo, Zhiyang Teng, Wei Lu, Shay B. Cohen, Zuozhu Liu, Lidong Bing

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

An Energy-efficient Multi-core Restricted Boltzmann Machine Processor with On-chip Bio-plausible Learning and Reconfigurable Sparsity.

Jiajun Wu, Xuan Huang, Le Yang, Liang Wang, Jipeng Wang, Zuozhu Liu, Kwen-Siong Chong, Shaowei Lin, Chao Wang

Proceedings of the IEEE Asian Solid-State Circuits Conference, 2020

Biologically Plausible Sequence Learning with Spiking Neural Networks.

Zuozhu Liu, Thiparat Chotibut, Christopher Hillar, Shaowei Lin

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Attention-based Graph Convolutional Network for Recommendation System.

Chenyuan Feng, Zuozhu Liu, Shaowei Lin, Tony Q. S. Quek

Proceedings of the IEEE International Conference on Acoustics, 2019

2018

Variational Probability Flow for Biologically Plausible Training of Deep Neural Networks.

Zuozhu Liu, Tony Q. S. Quek, Shaowei Lin

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Heterogeneous Sensor Data Fusion By Deep Multimodal Encoding.

Zuozhu Liu, Wenyu Zhang, Shaowei Lin, Tony Q. S. Quek

IEEE J. Sel. Top. Signal Process., 2017

Vprop: Variational Inference using RMSprop.

Mohammad Emtiyaz Khan, Zuozhu Liu, Voot Tangkaratt, Yarin Gal

CoRR, 2017

Variational Adaptive-Newton Method for Explorative Learning.

Mohammad Emtiyaz Khan, Wu Lin, Voot Tangkaratt, Zuozhu Liu, Didrik Nielsen

CoRR, 2017

Deep fusion of heterogeneous sensor data.

Zuozhu Liu, Wenyu Zhang, Tony Q. S. Quek, Shaowei Lin

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2015

Concept hierarchies and human navigation.

Salvador Aguiñaga, Aditya Nambiar, Zuozhu Liu, Tim Weninger

Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015