Two-Stream Multi-Task Network for Fashion Recognition. - Peizhao Li; Yanjing Li; Xiaolong Jiang; Xiantong Zhen (ICIP, 2019)

Model-Free Tracking With Deep Appearance and Motion Features Integration. - Xiaolong Jiang; Peizhao Li; Xiantong Zhen; Xianbin Cao 001 (WACV, 2019)

Multi-Scale Aggregation Network for Direct Face Alignment. - Peizhao Li; Anran Zhang; Lei Yue; Xiantong Zhen; Xianbin Cao 001 (WACV, 2019)

Graph Neural Based End-to-end Data Association Framework for Online Multiple-Object Tracking. - Xiaolong Jiang; Peizhao Li; Yanjing Li; Xiantong Zhen (CoRR, 2019)

Deep Fair Clustering for Visual Learning. - Peizhao Li; Han Zhao 002; Hongfu Liu 001 (CVPR, 2020)

Phase Shifter-Relaxed and Control-Relaxed Continuous Steering Multiple Beamforming 4 × 4 Butler Matrix Phased Array. - Han Ren; Peizhao Li; Yixin Gu; Bayaner Arigong (IEEE Trans. Circuits Syst., 2020)

SelfDoc: Self-Supervised Document Representation Learning. - Peizhao Li; Jiuxiang Gu; Jason Kuen; Vlad I. Morariu; Handong Zhao; Rajiv Jain; Varun Manjunatha; Hongfu Liu 001 (CVPR, 2021)

On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections. - Peizhao Li; Yifei Wang 002; Han Zhao 002; Pengyu Hong; Hongfu Liu 001 (ICLR, 2021)

Deep Clustering based Fair Outlier Detection. - Hanyu Song; Peizhao Li; Hongfu Liu 001 (KDD, 2021)

Exploiting Temporal Relations on Radar Perception for Autonomous Driving. - Peizhao Li; Pu Wang 004; Karl Berntorp; Hongfu Liu 001 (CVPR, 2022)

Achieving Fairness at No Utility Cost via Data Reweighing with Influence. - Peizhao Li; Hongfu Liu 001 (ICML, 2022)

Achieving Fairness at No Utility Cost via Data Reweighing. - Peizhao Li; Hongfu Liu 001 (CoRR, 2022)

Mining Label Distribution Drift in Unsupervised Domain Adaptation. - Peizhao Li; Zhengming Ding; Hongfu Liu 001 (AI (1), 2023)

Characterizing the Influence of Graph Elements. - Zizhang Chen; Peizhao Li; Hongfu Liu 001; Pengyu Hong (ICLR, 2023)

Robust Fair Clustering: A Novel Fairness Attack and Defense Framework. - Anshuman Chhabra; Peizhao Li; Prasant Mohapatra; Hongfu Liu 001 (ICLR, 2023)

Learning Antidote Data to Individual Unfairness. - Peizhao Li; Ethan Xia; Hongfu Liu 001 (ICML, 2023)

Dual Node and Edge Fairness-Aware Graph Partition. - Tingwei Liu; Peizhao Li; Hongfu Liu 001 (CoRR, 2023)

UniAR: Unifying Human Attention and Response Prediction on Visual Content. - Peizhao Li; Junfeng He; Gang Li; Rachit Bhargava; Shaolei Shen; Nachiappan Valliappan; Youwei Liang; Hongxiang Gu; Venky Ramachandran; Golnaz Farhadi; Yang Li; Kai J. Kohlhoff; et al. (CoRR, 2023)

Rich Human Feedback for Text-to-Image Generation. - Youwei Liang; Junfeng He; Gang Li; Peizhao Li; Arseniy Klimovskiy; Nicholas Carolan; Jiao Sun; Jordi Pont-Tuset; Sarah Young; Feng Yang; Junjie Ke; Krishnamurthy Dj Dvijotham; et al. (CVPR, 2024)

MMVR: Millimeter-Wave Multi-view Radar Dataset and Benchmark for Indoor Perception. - Mohammad Mahbubur Rahman; Ryoma Yataka; Sorachi Kato; Pu Wang 004; Peizhao Li; Adriano Cardace; Petros Boufounos (ECCV (79), 2024)

"What Data Benefits My Classifier?" Enhancing Model Performance and Interpretability through Influence-Based Data Selection. - Anshuman Chhabra; Peizhao Li; Prasant Mohapatra; Hongfu Liu 001 (ICLR, 2024)

UniAR: A Unified model for predicting human Attention and Responses on visual content. - Peizhao Li; Junfeng He; Gang Li; Rachit Bhargava; Shaolei Shen; Nachiappan Valliappan; Youwei Liang; Hongxiang Gu; Venky Ramachandran; Golnaz Farhadi; Yang Li; Kai Kohlhoff; et al. (NeurIPS, 2024)

Adaptive edge prior-based deep attention residual network for low-dose CT image denoising. - Tong Wu; Peizhao Li; Jie Sun; Binh P. Nguyen (Biomed. Signal Process. Control., 2024)

BlenderLLM: Training Large Language Models for Computer-Aided Design with Self-improvement. - Yuhao Du; Shunian Chen; Wenbo Zan; Peizhao Li; Mingxuan Wang; Dingjie Song; Bo Li; Yan Hu; Benyou Wang (CoRR, 2024)

Patent lifetime prediction using LightGBM with a customized loss. - Jieming Liu; Peizhao Li; Xiaowei Liu (PeerJ Comput. Sci., 2024)

Uncertainty Quantification for Clinical Outcome Predictions with (Large) Language Models. - Zizhang Chen; Peizhao Li; Xiaomeng Dong; Pengyu Hong (NAACL (Findings), 2025)

Performance investigation on disaggregated artificial intelligence data centers beyond rack scale with optical switching. - Fulong Yan; Hanting Huang; Yanxian Bi; Peizhao Li; Zhiwen Xue; Chao Li; Zichen Liu; Zhixue He; Zihao Li; Qidong Cao (J. Opt. Commun. Netw., 2025)