Publications

Selected Publications (* for corresponding author, # for co-first author)

Preprint

Med-U1: Incentivizing Unified Medical Reasoning in LLMs via Large-scale Reinforcement Learning
Xiaotian Zhang, Yuan Wang, Zhaopeng Feng, Ruizhe Chen, Zhijie Zhou, Yan Zhang, Hongxia Xu, Jian Wu, Zuozhu Liu*.

arXiv

Code

Data

2025

DiffPO: Diffusion-styled Preference Optimization for Inference Time Alignment of Large Language Models.
Ruizhe Chen, Wenhao Chai, Zhifei Yang, Xiaotian Zhang, Ziyang Wang, Tony Quek, Joey Tianyi Zhou, Soujanya Poria, Zuozhu Liu*.
ACL 2025.

arXiv

Code

Data

Mitigating Posterior Salience Attenuation in Long-Context LLMs with Positional Contrastive Decoding.
Zikai Xiao, Ziyang Wang, Wen MA, Yan Zhang, Wei Shen, WangYan, Luqi Gong, Zuozhu Liu*.
ACL 2025.

arXiv

Code

Data

HSCR: Hierarchical Self-Contrastive Rewarding for Aligning Medical Vision Language Models.
Songtao Jiang, Yan Zhang, Yeying Jin, Zhihang Tang, Yangyang Wu, YANG FENG, Jian Wu, Zuozhu Liu*.
ACL 2025.

arXiv

Code

Data

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering.
Yichen Li, Zhiting Fan, Ruizhe Chen, Xiaotang Gai, Luqi Gong, Yan Zhang, Zuozhu Liu*.
Findings of ACL 2025.

arXiv

Code

Data

M-MAD: Multidimensional Multi-Agent Debate for Advanced Machine Translation Evaluation.
Zhaopeng Feng, Jiayuan Su, Jiamei Zheng, Jiahan Ren, Yan Zhang, Jian Wu, Hongwei Wang, Zuozhu Liu*.
ACL 2025.

arXiv

Code

Data

FairMT-Bench: Benchmarking Fairness for Multi-turn Dialogue in Conversational LLMs.
Zhiting Fan, Ruizhe Chen, Tianxiang Hu, and Zuozhu Liu*.
ICLR (Spotlight), 2025.

arXiv

Code

Data

PAD: Personalized Alignment at Decoding-time.
Ruizhe Chen, Xiaotian Zhang, Meng Luo, Wenhao Chai, and Zuozhu Liu*.
ICLR, 2025.

arXiv

Code

Data

SynCamMaster: Synchronizing Multi-Camera Video Generation from Diverse Viewpoints.
Jianhong Bai, Menghan Xia, Xintao Wang, Ziyang Yuan, Zuozhu Liu, Haoji Hu, Pengfei Wan, Di ZHANG.
ICLR, 2025.

arXiv

Code

Data

TEaR: Improving LLM-based Machine Translation with Systematic Self-Refinement.
Zhaopeng Feng, Yan Zhang, Hao Li, Bei Wu, Jiayu Liao, Wenqiang Liu, Jun Lang, YANG FENG, Jian Wu, and Zuozhu Liu*.
NAACL-Findings, 2025.

arXiv

Code

Data

MedThink: A Rationale-Guided Framework for Explaining Medical Visual Question Answering.
Xiaotang Gai, Chenyi Zhou, Jiaxiang Liu, YANG FENG, Jian Wu, and Zuozhu Liu*.
NAACL-Findings, 2025.

arXiv

Code

Data

Identifying and Mitigating Social Bias Knowledge in Language Models.
Ruizhe Chen, Yichen Li, Jianfei Yang, YANG FENG, Joey Tianyi Zhou, Jian Wu, and Zuozhu Liu*.
NAACL-Findings, 2025.

arXiv

Code

Data

KPL: Training-Free Medical Knowledge Mining of Vision-Language Models.
Jiaxiang Liu, Tianxiang Hu, Jiawei Du, Ruiyuan Zhang, Joey Tianyi Zhou, and Zuozhu Liu*.
AAAI (Oral), 2025.

arXiv

Code

Data

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.

Paper

Code

Data

MedCoT: Medical Chain of Thought via Hierarchical Expert.
Jiaxiang Liu, Yuan Wang, Jiawei Du, Joey Tianyi Zhou and Zuozhu Liu*.
EMNLP, 2024.

arXiv

Code

Data

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.

arXiv

Code

Data

BiasAlert: A Plug-and-play Tool for Social Bias Detection in LLMs.
Zhiting Fan, Ruizhe Chen, Ruiling Xu and Zuozhu Liu*.
EMNLP, 2024.

arXiv

Code

Data

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.

arXiv

Code

Data

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.

arXiv

Code

Data

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.

Paper

Code

Data

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.

Paper

Code

Data

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.

arXiv

Code

Data

Learnable Privacy Neurons Localization in Language Models.
R.Chen, T. Hu, Y. Feng and Zuozhu Liu*.
ACL 2024.

arXiv

Code

Data

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.

arXiv

Code

Data

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.

Paper

Code

Data

2023

Empirical Study of Zero-shot NER with ChatGPT.
T. Xie, Q. Li, J. Zhang, Y. Zhang, Zuozhu Liu, H. Wang.
EMNLP 2023.

arXiv

Code

Data

How Well Do Text Embedding Models Understand Syntax?
Y. Zhang, Z. Feng, Z. Teng, Zuozhu Liu*, H. Li.
EMNLP 2023.

arXiv

Code

Data

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.

arXiv

Code

Data

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.

arXiv

Code

Data

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.

arXiv

Code

Data

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.

Paper

Code

Data

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.

Paper

Code

Data

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.

arXiv

Code

Data

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.

arXiv

Code

Data

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.