Reducing Overfitting in Deep Convolutional Neural Networks Using Redundancy Regularizer. - Bingzhe Wu; Zhichao Liu; Zhihang Yuan; Guangyu Sun 003; Charles Wu (ICANN (2), 2017)

SRPGAN: Perceptual Generative Adversarial Network for Single Image Super Resolution. - Bingzhe Wu; Haodong Duan; Zhichao Liu; Guangyu Sun 003 (CoRR, 2017)

G2C: A Generator-to-Classifier Framework Integrating Multi-Stained Visual Cues for Pathological Glomerulus Classification. - Bingzhe Wu; Xiaolu Zhang; Shiwan Zhao; Lingxi Xie; Caihong Zeng; Zhihong Liu; Guangyu Sun 003 (AAAI, 2019)

P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification. - Bingzhe Wu; Shiwan Zhao; Guangyu Sun 003; Xiaolu Zhang; Zhong Su; Caihong Zeng; Zhihong Liu (CVPR, 2019)

BAYHENN: Combining Bayesian Deep Learning and Homomorphic Encryption for Secure DNN Inference. - Peichen Xie; Bingzhe Wu; Guangyu Sun 003 (IJCAI, 2019)

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection. - Bingzhe Wu; Shiwan Zhao; Chaochao Chen 001; Haoyang Xu; Li Wang 056; Xiaolu Zhang; Guangyu Sun 003; Jun Zhou 011 (NeurIPS, 2019)

Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics. - Bingzhe Wu; Chaochao Chen 001; Shiwan Zhao; Cen Chen 001; Yuan Yao; Guangyu Sun 003; Li Wang 056; Xiaolu Zhang; Jun Zhou 011 (AAAI, 2020)

Nebula: A Scalable Privacy-Preserving Machine Learning System in Ant Financial. - Cen Chen 001; Bingzhe Wu; Li Wang 056; Chaochao Chen 001; Jin Tan; Lei Wang 152; Jun Zhou 011; Benyu Zhang (CIKM, 2020)

Secure Social Recommendation Based on Secret Sharing. - Chaochao Chen 001; Liang Li; Bingzhe Wu; Cheng Hong 001; Li Wang 056; Jun Zhou 011 (ECAI, 2020)

S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search. - Zhihang Yuan; Bingzhe Wu; Guangyu Sun 003; Zheng Liang 003; Shiwan Zhao; Weichen Bi (ECCV (2), 2020)

SaFace: Towards Scenario-aware Face Recognition via Edge Computing System. - Zhe Zhou 002; Bingzhe Wu; Zheng Liang 003; Guangyu Sun 003; Chenren Xu; Guojie Luo (HotEdge, 2020)

Automatic Knowledge Fusion in Transferrable Networks for Semantic Text Matching. - Cen Chen 001; Ya-Lin Zhang 001; Minghui Qiu; Bingzhe Wu; Li Wang 056; Longfei Li; Jun Zhou 011 (WWW (Companion Volume), 2020)

Practical Privacy Preserving POI Recommendation. - Chaochao Chen 001; Bingzhe Wu; Wenjin Fang; Jun Zhou 011; Li Wang 056; Yuan Qi 001; Xiaolin Zheng (CoRR, 2020)

Industrial Scale Privacy Preserving Deep Neural Network. - Longfei Zheng; Chaochao Chen 001; Yingting Liu; Bingzhe Wu; Xibin Wu; Li Wang 056; Lei Wang 152; Jun Zhou 011; Shuang Yang (CoRR, 2020)

Privacy-Preserving Graph Neural Network for Node Classification. - Jun Zhou 011; Chaochao Chen 001; Longfei Zheng; Xiaolin Zheng; Bingzhe Wu; Ziqi Liu; Li Wang 056 (CoRR, 2020)

A Comprehensive Analysis of Information Leakage in Deep Transfer Learning. - Cen Chen 001; Bingzhe Wu; Minghui Qiu; Li Wang 057; Jun Zhou 011 (CoRR, 2020)

ENAS4D: Efficient Multi-stage CNN Architecture Search for Dynamic Inference. - Zhihang Yuan; Xin Liu 073; Bingzhe Wu; Guangyu Sun 003 (CoRR, 2020)

S3ML: A Secure Serving System for Machine Learning Inference. - Junming Ma; Chaofan Yu; Aihui Zhou; Bingzhe Wu; Xibin Wu; Xingyu Chen; Xiangqun Chen; Lei Wang 152; Donggang Cao (CoRR, 2020)

Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design. - Chaochao Chen 001; Jun Zhou 011; Longfei Zheng; Yan Wang 002; Xiaolin Zheng; Bingzhe Wu; Cen Chen 001; Li Wang 056; Jianwei Yin (CoRR, 2020)

Practical Privacy Preserving POI Recommendation. - Chaochao Chen 001; Jun Zhou 011; Bingzhe Wu; Wenjing Fang; Li Wang 056; Yuan Qi 001; Xiaolin Zheng (ACM Trans. Intell. Syst. Technol., 2020)

HASCO: Towards Agile HArdware and Software CO-design for Tensor Computation. - Qingcheng Xiao; Size Zheng 001; Bingzhe Wu; Pengcheng Xu 005; Xuehai Qian; Yun Liang 001 (ISCA, 2021)

NAS4RRAM: neural network architecture search for inference on RRAM-based accelerators. - Zhihang Yuan; Jingze Liu; Xingchen Li; Longhao Yan; Haoxiang Chen 003; Bingzhe Wu; Yuchao Yang 001; Guangyu Sun 003 (Sci. China Inf. Sci., 2021)

Generalization Bounds for Stochastic Gradient Langevin Dynamics: A Unified View via Information Leakage Analysis. - Bingzhe Wu; Zhicong Liang; Yatao Bian; Chaochao Chen 001; Junzhou Huang; Yuan Yao (CoRR, 2021)

ASFGNN: Automated separated-federated graph neural network. - Longfei Zheng; Jun Zhou 011; Chaochao Chen 001; Bingzhe Wu; Li Wang 056; Benyu Zhang (Peer-to-Peer Netw. Appl., 2021)

Enabling High-Quality Uncertainty Quantification in a PIM Designed for Bayesian Neural Network. - Xingchen Li; Bingzhe Wu; Guangyu Sun 003; Zhe Zhang 006; Zhihang Yuan; Runsheng Wang; Ru Huang 001; Dimin Niu; Hongzhong Zheng; Zhichao Lu; Liang Zhao; Meng-Fan Marvin Chang; et al. (HPCA, 2022)

Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification. - Chaochao Chen 001; Jun Zhou 011; Longfei Zheng; Huiwen Wu; Lingjuan Lyu; Jia Wu 001; Bingzhe Wu; Ziqi Liu; Li Wang 056; Xiaolin Zheng (IJCAI, 2022)

Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. - Bingzhe Wu; Yatao Bian; Hengtong Zhang; Jintang Li; Junchi Yu; Liang Chen 001; Chaochao Chen 001; Junzhou Huang (KDD, 2022)

UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup. - Zongbo Han; Zhipeng Liang; Fan Yang 081; Liu Liu 014; Lanqing Li; Yatao Bian; Peilin Zhao; Bingzhe Wu; Changqing Zhang; Jianhua Yao 001 (NeurIPS, 2022)

DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations. - Yuanfeng Ji; Lu Zhang 060; Jiaxiang Wu 001; Bingzhe Wu; Long-Kai Huang; Tingyang Xu; Yu Rong 001; Lanqing Li; Jie Ren; Ding Xue; Houtim Lai; Shaoyong Xu; et al. (CoRR, 2022)

Recent Advances in Reliable Deep Graph Learning: Adversarial Attack, Inherent Noise, and Distribution Shift. - Bingzhe Wu; Jintang Li; Chengbin Hou; Guoji Fu; Yatao Bian; Liang Chen 001; Junzhou Huang (CoRR, 2022)

DRFLM: Distributionally Robust Federated Learning with Inter-client Noise via Local Mixup. - Bingzhe Wu; Zhipeng Liang; Yuxuan Han; Yatao Bian; Peilin Zhao; Junzhou Huang (CoRR, 2022)

A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. - Bingzhe Wu; Jintang Li; Junchi Yu; Yatao Bian; Hengtong Zhang; Chaochao Chen 001; Chengbin Hou; Guoji Fu; Liang Chen 001; Tingyang Xu; Yu Rong 001; Xiaolin Zheng; et al. (CoRR, 2022)

ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug Discovery. - Lanqing Li; Liang Zeng 002; Ziqi Gao; Shen Yuan; Yatao Bian; Bingzhe Wu; Hengtong Zhang; Chan Lu; Yang Yu 010; Wei Liu 005; Hongteng Xu; Jia Li 009; et al. (CoRR, 2022)

Vertical Federated Linear Contextual Bandits. - Zeyu Cao; Zhipeng Liang; Shu Zhang 013; Hangyu Li 002; Ouyang Wen; Yu Rong 001; Peilin Zhao; Bingzhe Wu (CoRR, 2022)

Learning with Noisy Labels over Imbalanced Subpopulations. - Mingcai Chen; Yu Zhao 009; Bing He; Zongbo Han; Bingzhe Wu; Jianhua Yao 001 (CoRR, 2022)

Toward Scalable and Privacy-preserving Deep Neural Network via Algorithmic-Cryptographic Co-design. - Jun Zhou 011; Longfei Zheng; Chaochao Chen 001; Yan Wang 002; Xiaolin Zheng; Bingzhe Wu; Cen Chen 001; Li Wang 056; Jianwei Yin (ACM Trans. Intell. Syst. Technol., 2022)

DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - a Focus on Affinity Prediction Problems with Noise Annotations. - Yuanfeng Ji; Lu Zhang 060; Jiaxiang Wu 001; Bingzhe Wu; Lanqing Li; Long-Kai Huang; Tingyang Xu; Yu Rong 001; Jie Ren; Ding Xue; Houtim Lai; Wei Liu 005; et al. (AAAI, 2023)

E-NER: Evidential Deep Learning for Trustworthy Named Entity Recognition. - Zhen Zhang 048; Mengting Hu; Shiwan Zhao; Minlie Huang; Haotian Wang; Lemao Liu; Zhirui Zhang; Zhe Liu 001; Bingzhe Wu (ACL (Findings), 2023)

Attention Paper: How Generative AI Reshapes Digital Shadow Industry? - Qichao Wang; Huan Ma; Wentao Wei; Hangyu Li 002; Changqing Zhang; Peilin Zhao; Binwen Zhao; Bo Hu; Shu Zhang 013; Bingzhe Wu; Liang Chen 001 (ACM TUR-C, 2023)

SAILOR: Structural Augmentation Based Tail Node Representation Learning. - Jie Liao; Jintang Li; Liang Chen 001; Bingzhe Wu; Yatao Bian; Zibin Zheng (CIKM, 2023)

Post-Training Quantization on Diffusion Models. - Yuzhang Shang; Zhihang Yuan; Bin Xie; Bingzhe Wu; Yan Yan 002 (CVPR, 2023)

Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators. - Liang Chen 001; Yang Deng 002; Yatao Bian; Zeyu Qin; Bingzhe Wu; Tat-Seng Chua; Kam-Fai Wong (EMNLP, 2023)

RECAL: Sample-Relation Guided Confidence Calibration over Tabular Data. - Haotian Wang; Zhen Zhang 048; Mengting Hu; Qichao Wang; Liang Chen 001; Yatao Bian; Bingzhe Wu (EMNLP (Findings), 2023)

Density-Aware Prototypical Network for Few-Shot Relation Classification. - Jianfeng Wu; Mengting Hu; Yike Wu; Bingzhe Wu; Yalan Xie; Mingming Liu; Renhong Cheng (EMNLP (Findings), 2023)

PsyCoT: Psychological Questionnaire as Powerful Chain-of-Thought for Personality Detection. - Tao Yang 033; Tianyuan Shi; Fanqi Wan; Xiaojun Quan; Qifan Wang 001; Bingzhe Wu; Jiaxiang Wu 001 (EMNLP (Findings), 2023)

Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization. - Yongqiang Chen 002; Kaiwen Zhou; Yatao Bian; Binghui Xie; Bingzhe Wu; Yonggang Zhang 003; Kaili Ma 001; Han Yang 002; Peilin Zhao; Bo Han 003; James Cheng (ICLR, 2023)

Federated Nearest Neighbor Machine Translation. - Yichao Du; Zhirui Zhang; Bingzhe Wu; Lemao Liu; Tong Xu 001; Enhong Chen (ICLR, 2023)

Calibrating Multimodal Learning. - Huan Ma; Qingyang Zhang; Changqing Zhang; Bingzhe Wu; Huazhu Fu; Joey Tianyi Zhou; Qinghua Hu (ICML, 2023)

Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation. - Zeyu Cao; Zhipeng Liang; Bingzhe Wu; Shu Zhang 013; Hangyu Li 002; Ouyang Wen; Yu Rong 001; Peilin Zhao (KDD, 2023)

IIB-MIL: Integrated Instance-Level and Bag-Level Multiple Instances Learning with Label Disambiguation for Pathological Image Analysis. - Qin Ren 001; Yu Zhao 009; Bing He; Bingzhe Wu; Sijie Mai; Fan Xu; Yueshan Huang; Yonghong He; Junzhou Huang; Jianhua Yao 001 (MICCAI (6), 2023)

Fairness-guided Few-shot Prompting for Large Language Models. - Huan Ma; Changqing Zhang; Yatao Bian; Lemao Liu; Zhirui Zhang; Peilin Zhao; Shu Zhang 013; Huazhu Fu; Qinghua Hu; Bingzhe Wu (NeurIPS, 2023)

Benchmarking the Reliability of Post-training Quantization: a Particular Focus on Worst-case Performance. - Zhihang Yuan; Jiawei Liu 006; Jiaxiang Wu 001; Dawei Yang; Qiang Wu 012; Guangyu Sun 003; Wenyu Liu 001; Xinggang Wang; Bingzhe Wu (CoRR, 2023)

RPTQ: Reorder-based Post-training Quantization for Large Language Models. - Zhihang Yuan; Lin Niu; Jiawei Liu 006; Wenyu Liu 001; Xinggang Wang; Yuzhang Shang; Guangyu Sun 003; Qiang Wu 012; Jiaxiang Wu 001; Bingzhe Wu (CoRR, 2023)

SLPerf: a Unified Framework for Benchmarking Split Learning. - Tianchen Zhou; Zhanyi Hu; Bingzhe Wu; Cen Chen 001 (CoRR, 2023)

Reweighted Mixup for Subpopulation Shift. - Zongbo Han; Zhipeng Liang; Fan Yang 081; Liu Liu 014; Lanqing Li; Yatao Bian; Peilin Zhao; Qinghua Hu; Bingzhe Wu; Changqing Zhang; Jianhua Yao 001 (CoRR, 2023)

Attention Paper: How Generative AI Reshapes Digital Shadow Industry? - Qichao Wang; Huan Ma; Wentao Wei; Hangyu Li 002; Liang Chen 001; Peilin Zhao; Binwen Zhao; Bo Hu; Shu Zhang 013; Zibin Zheng; Bingzhe Wu (CoRR, 2023)

Uncertainty in Natural Language Processing: Sources, Quantification, and Applications. - Mengting Hu; Zhen Zhang 048; Shiwan Zhao; Minlie Huang; Bingzhe Wu (CoRR, 2023)

Semantic Equivariant Mixup. - Zongbo Han; Tianchi Xie; Bingzhe Wu; Qinghua Hu; Changqing Zhang (CoRR, 2023)

Is GPT4 a Good Trader? - Bingzhe Wu (CoRR, 2023)

VDC: Versatile Data Cleanser for Detecting Dirty Samples via Visual-Linguistic Inconsistency. - Zihao Zhu 001; Mingda Zhang; Shaokui Wei; Bingzhe Wu; Baoyuan Wu (CoRR, 2023)

Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning. - Huan Ma; Changqing Zhang; Huazhu Fu; Peilin Zhao; Bingzhe Wu (CoRR, 2023)

Language Agents for Detecting Implicit Stereotypes in Text-to-image Models at Scale. - Qichao Wang; Tian Bian; Yian Yin; Tingyang Xu; Hong Cheng 001; Helen M. Meng; Zibin Zheng; Liang Chen 001; Bingzhe Wu (CoRR, 2023)

X-Mark: Towards Lossless Watermarking Through Lexical Redundancy. - Liang Chen 001; Yatao Bian; Yang Deng 002; Shuaiyi Li; Bingzhe Wu; Peilin Zhao; Kam-Fai Wong (CoRR, 2023)

Dynamics Adapted Imitation Learning. - Zixuan Liu 002; Liu Liu 014; Bingzhe Wu; Lanqing Li; Xueqian Wang 001; Bo Yuan 008; Peilin Zhao (Trans. Mach. Learn. Res., 2023)

Lightweight Privacy-Preserving Federated Incremental Decision Trees. - Zhaoyang Han; Chunpeng Ge 001; Bingzhe Wu; Zhe Liu 001 (IEEE Trans. Serv. Comput., 2023)

COPPER: a combinatorial optimization problem solver with processing-in-memory architecture. - Qiankun Wang; Xingchen Li; Bingzhe Wu; Ke Yang; Wei Hu; Guangyu Sun 003; Yuchao Yang 001 (Frontiers Inf. Technol. Electron. Eng., 2023)

A Label Disambiguation-Based Multimodal Massive Multiple Instance Learning Approach for Immune Repertoire Classification. - Fan Xu; Yu Zhao 009; Bingzhe Wu; Yueshan Huang; Qin Ren 001; Yang Xiao; Bing He; Jie Zheng; Jianhua Yao 001 (AAAI, 2024)

VDC: Versatile Data Cleanser based on Visual-Linguistic Inconsistency by Multimodal Large Language Models. - Zihao Zhu 001; Mingda Zhang; Shaokui Wei; Bingzhe Wu; Baoyuan Wu (ICLR, 2024)

Parameter-Efficient Fine-Tuning with Discrete Fourier Transform. - Ziqi Gao; Qichao Wang; Aochuan Chen; Zijing Liu; Bingzhe Wu; Liang Chen 001; Jia Li 009 (ICML, 2024)

Rethinking the Reliability of Post-hoc Calibration Methods Under Subpopulation Shift. - Yan Zhu; Huan Ma; Changqing Zhang; Bingzhe Wu; Huazhu Fu; Joey Tianyi Zhou; Qinghua Hu (PRICAI (2), 2024)

Rethinking and Simplifying Bootstrapped Graph Latents. - Wangbin Sun; Jintang Li; Liang Chen 001; Bingzhe Wu; Yatao Bian; Zibin Zheng (WSDM, 2024)

Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping. - Haoyu Wang 003; Guozheng Ma; Ziqiao Meng; Zeyu Qin; Li Shen 008; Zhong Zhang; Bingzhe Wu; Liu Liu 014; Yatao Bian; Tingyang Xu; Xueqian Wang 001; Peilin Zhao (CoRR, 2024)

LLM Inference Unveiled: Survey and Roofline Model Insights. - Zhihang Yuan; Yuzhang Shang; Yang Zhou; Zhen Dong 003; Zhe Zhou 002; Chenhao Xue; Bingzhe Wu; Zhikai Li; Qingyi Gu; Yong Jae Lee; Yan Yan 002; Beidi Chen; et al. (CoRR, 2024)

Invariant Test-Time Adaptation for Vision-Language Model Generalization. - Huan Ma; Yan Zhu; Changqing Zhang; Peilin Zhao; Baoyuan Wu; Long-Kai Huang; Qinghua Hu; Bingzhe Wu (CoRR, 2024)

RiskAwareBench: Towards Evaluating Physical Risk Awareness for High-level Planning of LLM-based Embodied Agents. - Zihao Zhu 001; Bingzhe Wu; Zhengyou Zhang; Baoyuan Wu (CoRR, 2024)

Probing the Safety Response Boundary of Large Language Models via Unsafe Decoding Path Generation. - Haoyu Wang 003; Bingzhe Wu; Yatao Bian; Yongzhe Chang; Xueqian Wang 001; Peilin Zhao (CoRR, 2024)

Variate Associated Domain Adaptation for Unsupervised Multivariate Time Series Anomaly Detection. - Yifan He 005; Yatao Bian; Xi Ding; Bingzhe Wu; Jihong Guan; Ji Zhang 001; Shuigeng Zhou (ACM Trans. Knowl. Discov. Data, 2024)

Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Model. - Huan Ma; Yan Zhu; Changqing Zhang; Peilin Zhao; Baoyuan Wu; Long-Kai Huang; Qinghua Hu; Bingzhe Wu (AAAI, 2025)

SLPerf: A Research Library and Benchmark Framework for Split Learning. - Zhanyi Hu; Tianchen Zhou; Bingzhe Wu; Cen Chen 001; Yanhao Wang 001 (ICDEW, 2025)

A Review and Experimental Evaluation on Split Learning. - Zhanyi Hu; Tianchen Zhou; Bingzhe Wu; Cen Chen 001; Yanhao Wang 001 (Future Internet, 2025)

Measuring Diversity in Synthetic Datasets. - Yuchang Zhu; Huizhe Zhang; Bingzhe Wu; Jintang Li; Zibin Zheng; Peilin Zhao; Liang Chen 001; Yatao Bian (CoRR, 2025)

Learning With Noisy Labels Over Imbalanced Subpopulations. - Mingcai Chen; Yu Zhao 009; Bing He; Zongbo Han; Junzhou Huang; Bingzhe Wu; Jianhua Yao 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)

Sparsification and Reconstruction from the Perspective of Representation Geometry. - Wenjie Sun; Bingzhe Wu; Zhile Yang; Chengke Wu 002 (CoRR, 2025)

NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction. - Qichao Wang; Ziqiao Meng; Wenqian Cui; Yifei Zhang; Pengcheng Wu; Bingzhe Wu; Irwin King; Liang Chen 001; Peilin Zhao (CoRR, 2025)

SAFEx: Analyzing Vulnerabilities of MoE-Based LLMs via Stable Safety-critical Expert Identification. - ZhengLin Lai; MengYao Liao; Dong Xu 023; Zebin Zhao 007; Zhihang Yuan; Chao Fan; Jianqiang Li; Bingzhe Wu (CoRR, 2025)