Bingzhe Wu

According to our database, Bingzhe Wu authored at least 71 papers between 2017 and 2024.

Collaborative distances:

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

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

LLM Inference Unveiled: Survey and Roofline Model Insights.

Zhihang Yuan, Yuzhang Shang, Yang Zhou, Zhen Dong, Zhe Zhou, Chenhao Xue, Bingzhe Wu, Zhikai Li, Qingyi Gu, Yong Jae Lee, Yan Yan, Beidi Chen, Guangyu Sun, Kurt Keutzer

CoRR, 2024

Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping.

Haoyu Wang, Guozheng Ma, Ziqiao Meng, Zeyu Qin, Li Shen, Zhong Zhang, Bingzhe Wu, Liu Liu, Yatao Bian, Tingyang Xu, Xueqian Wang, Peilin Zhao

CoRR, 2024

Rethinking and Simplifying Bootstrapped Graph Latents.

Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

A Label Disambiguation-Based Multimodal Massive Multiple Instance Learning Approach for Immune Repertoire Classification.

Fan Xu, Yu Zhao, Bingzhe Wu, Yueshan Huang, Qin Ren, Yang Xiao, Bing He, Jie Zheng, Jianhua Yao

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

2023

COPPER: a combinatorial optimization problem solver with processing-in-memory architecture.

Qiankun Wang, Xingchen Li, Bingzhe Wu, Ke Yang, Wei Hu, Guangyu Sun, Yuchao Yang

Frontiers Inf. Technol. Electron. Eng., May, 2023

Lightweight Privacy-Preserving Federated Incremental Decision Trees.

Zhaoyang Han, Chunpeng Ge, Bingzhe Wu, Zhe Liu

IEEE Trans. Serv. Comput., 2023

X-Mark: Towards Lossless Watermarking Through Lexical Redundancy.

Liang Chen, Yatao Bian, Yang Deng, Shuaiyi Li, Bingzhe Wu, Peilin Zhao, Kam-Fai Wong

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, Helen M. Meng, Zibin Zheng, Liang Chen, Bingzhe Wu

CoRR, 2023

Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators.

Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong

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

VDC: Versatile Data Cleanser for Detecting Dirty Samples via Visual-Linguistic Inconsistency.

Zihao Zhu, Mingda Zhang, Shaokui Wei, Bingzhe Wu, Baoyuan Wu

CoRR, 2023

Is GPT4 a Good Trader?

Bingzhe Wu

CoRR, 2023

Semantic Equivariant Mixup.

Zongbo Han, Tianchi Xie, Bingzhe Wu, Qinghua Hu, Changqing Zhang

CoRR, 2023

Uncertainty in Natural Language Processing: Sources, Quantification, and Applications.

Mengting Hu, Zhen Zhang, Shiwan Zhao, Minlie Huang, Bingzhe Wu

CoRR, 2023

Attention Paper: How Generative AI Reshapes Digital Shadow Industry?

Qichao Wang, Huan Ma, Wentao Wei, Hangyu Li, Liang Chen, Peilin Zhao, Binwen Zhao, Bo Hu, Shu Zhang, Zibin Zheng, Bingzhe Wu

CoRR, 2023

Reweighted Mixup for Subpopulation Shift.

Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Qinghua Hu, Bingzhe Wu, Changqing Zhang, Jianhua Yao

CoRR, 2023

SLPerf: a Unified Framework for Benchmarking Split Learning.

Tianchen Zhou, Zhanyi Hu, Bingzhe Wu, Cen Chen

CoRR, 2023

RPTQ: Reorder-based Post-training Quantization for Large Language Models.

Zhihang Yuan, Lin Niu, Jiawei Liu, Wenyu Liu, Xinggang Wang, Yuzhang Shang, Guangyu Sun, Qiang Wu, Jiaxiang Wu, Bingzhe Wu

CoRR, 2023

Benchmarking the Reliability of Post-training Quantization: a Particular Focus on Worst-case Performance.

Zhihang Yuan, Jiawei Liu, Jiaxiang Wu, Dawei Yang, Qiang Wu, Guangyu Sun, Wenyu Liu, Xinggang Wang, Bingzhe Wu

CoRR, 2023

Fairness-guided Few-shot Prompting for Large Language Models.

Huan Ma, Changqing Zhang, Yatao Bian, Lemao Liu, Zhirui Zhang, Peilin Zhao, Shu Zhang, Huazhu Fu, Qinghua Hu, Bingzhe Wu

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

IIB-MIL: Integrated Instance-Level and Bag-Level Multiple Instances Learning with Label Disambiguation for Pathological Image Analysis.

Qin Ren, Yu Zhao, Bing He, Bingzhe Wu, Sijie Mai, Fan Xu, Yueshan Huang, Yonghong He, Junzhou Huang, Jianhua Yao

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

Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation.

Zeyu Cao, Zhipeng Liang, Bingzhe Wu, Shu Zhang, Hangyu Li, Ouyang Wen, Yu Rong, Peilin Zhao

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Calibrating Multimodal Learning.

Huan Ma, Qingyang Zhang, Changqing Zhang, Bingzhe Wu, Huazhu Fu, Joey Tianyi Zhou, Qinghua Hu

Proceedings of the International Conference on Machine Learning, 2023

Federated Nearest Neighbor Machine Translation.

Yichao Du, Zhirui Zhang, Bingzhe Wu, Lemao Liu, Tong Xu, Enhong Chen

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization.

Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Bingzhe Wu, Yonggang Zhang, Kaili Ma, Han Yang, Peilin Zhao, Bo Han, James Cheng

Proceedings of the Eleventh International Conference on Learning Representations, 2023

PsyCoT: Psychological Questionnaire as Powerful Chain-of-Thought for Personality Detection.

Tao Yang, Tianyuan Shi, Fanqi Wan, Xiaojun Quan, Qifan Wang, Bingzhe Wu, Jiaxiang Wu

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

Density-Aware Prototypical Network for Few-Shot Relation Classification.

Jianfeng Wu, Mengting Hu, Yike Wu, Bingzhe Wu, Yalan Xie, Mingming Liu, Renhong Cheng

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

RECAL: Sample-Relation Guided Confidence Calibration over Tabular Data.

Haotian Wang, Zhen Zhang, Mengting Hu, Qichao Wang, Liang Chen, Yatao Bian, Bingzhe Wu

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

Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators.

Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong

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

Post-Training Quantization on Diffusion Models.

Yuzhang Shang, Zhihang Yuan, Bin Xie, Bingzhe Wu, Yan Yan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

SAILOR: Structural Augmentation Based Tail Node Representation Learning.

Jie Liao, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Attention Paper: How Generative AI Reshapes Digital Shadow Industry?

Qichao Wang, Huan Ma, Wentao Wei, Hangyu Li, Changqing Zhang, Peilin Zhao, Binwen Zhao, Bo Hu, Shu Zhang, Bingzhe Wu, Liang Chen

Proceedings of the ACM Turing Award Celebration Conference - China 2023, 2023

E-NER: Evidential Deep Learning for Trustworthy Named Entity Recognition.

Zhen Zhang, Mengting Hu, Shiwan Zhao, Minlie Huang, Haotian Wang, Lemao Liu, Zhirui Zhang, Zhe Liu, Bingzhe Wu

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

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, Jiaxiang Wu, Bingzhe Wu, Lanqing Li, Long-Kai Huang, Tingyang Xu, Yu Rong, Jie Ren, Ding Xue, Houtim Lai, Wei Liu, Junzhou Huang, Shuigeng Zhou, Ping Luo, Peilin Zhao, Yatao Bian

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Toward Scalable and Privacy-preserving Deep Neural Network via Algorithmic-Cryptographic Co-design.

Jun Zhou, Longfei Zheng, Chaochao Chen, Yan Wang, Xiaolin Zheng, Bingzhe Wu, Cen Chen, Li Wang, Jianwei Yin

ACM Trans. Intell. Syst. Technol., 2022

Learning with Noisy Labels over Imbalanced Subpopulations.

Mingcai Chen, Yu Zhao, Bing He, Zongbo Han, Bingzhe Wu, Jianhua Yao

CoRR, 2022

Vertical Federated Linear Contextual Bandits.

Zeyu Cao, Zhipeng Liang, Shu Zhang, Hangyu Li, Ouyang Wen, Yu Rong, Peilin Zhao, Bingzhe Wu

CoRR, 2022

ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug Discovery.

Lanqing Li, Liang Zeng, Ziqi Gao, Shen Yuan, Yatao Bian, Bingzhe Wu, Hengtong Zhang, Chan Lu, Yang Yu, Wei Liu, Hongteng Xu, Jia Li, Peilin Zhao, Pheng-Ann Heng

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, Chengbin Hou, Guoji Fu, Liang Chen, Tingyang Xu, Yu Rong, Xiaolin Zheng, Junzhou Huang, Ran He, Baoyuan Wu, Guangyu Sun, Peng Cui, Zibin Zheng, Zhe Liu, Peilin Zhao

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

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, Junzhou Huang

CoRR, 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, Jiaxiang Wu, Bingzhe Wu, Long-Kai Huang, Tingyang Xu, Yu Rong, Lanqing Li, Jie Ren, Ding Xue, Houtim Lai, Shaoyong Xu, Jing Feng, Wei Liu, Ping Luo, Shuigeng Zhou, Junzhou Huang, Peilin Zhao, Yatao Bian

CoRR, 2022

UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup.

Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection.

Bingzhe Wu, Yatao Bian, Hengtong Zhang, Jintang Li, Junchi Yu, Liang Chen, Chaochao Chen, Junzhou Huang

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification.

Chaochao Chen, Jun Zhou, Longfei Zheng, Huiwen Wu, Lingjuan Lyu, Jia Wu, Bingzhe Wu, Ziqi Liu, Li Wang, Xiaolin Zheng

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Enabling High-Quality Uncertainty Quantification in a PIM Designed for Bayesian Neural Network.

Xingchen Li, Bingzhe Wu, Guangyu Sun, Zhe Zhang, Zhihang Yuan, Runsheng Wang, Ru Huang, Dimin Niu, Hongzhong Zheng, Zhichao Lu, Liang Zhao, Meng-Fan Marvin Chang, Tianchan Guan, Xin Si

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2022

2021

ASFGNN: Automated separated-federated graph neural network.

Longfei Zheng, Jun Zhou, Chaochao Chen, Bingzhe Wu, Li Wang, Benyu Zhang

Peer-to-Peer Netw. Appl., 2021

Generalization Bounds for Stochastic Gradient Langevin Dynamics: A Unified View via Information Leakage Analysis.

Bingzhe Wu, Zhicong Liang, Yatao Bian, Chaochao Chen, Junzhou Huang, Yuan Yao

CoRR, 2021

NAS4RRAM: neural network architecture search for inference on RRAM-based accelerators.

Zhihang Yuan, Jingze Liu, Xingchen Li, Longhao Yan, Haoxiang Chen, Bingzhe Wu, Yuchao Yang, Guangyu Sun

Sci. China Inf. Sci., 2021

HASCO: Towards Agile HArdware and Software CO-design for Tensor Computation.

Qingcheng Xiao, Size Zheng, Bingzhe Wu, Pengcheng Xu, Xuehai Qian, Yun Liang

Proceedings of the 48th ACM/IEEE Annual International Symposium on Computer Architecture, 2021

2020

Practical Privacy Preserving POI Recommendation.

Chaochao Chen, Jun Zhou, Bingzhe Wu, Wenjing Fang, Li Wang, Yuan Qi, Xiaolin Zheng

ACM Trans. Intell. Syst. Technol., 2020

Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design.

Chaochao Chen, Jun Zhou, Longfei Zheng, Yan Wang, Xiaolin Zheng, Bingzhe Wu, Cen Chen, Li Wang, Jianwei Yin

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, Donggang Cao

CoRR, 2020

ENAS4D: Efficient Multi-stage CNN Architecture Search for Dynamic Inference.

Zhihang Yuan, Xin Liu, Bingzhe Wu, Guangyu Sun

CoRR, 2020

A Comprehensive Analysis of Information Leakage in Deep Transfer Learning.

Cen Chen, Bingzhe Wu, Minghui Qiu, Li Wang, Jun Zhou

CoRR, 2020

Privacy-Preserving Graph Neural Network for Node Classification.

Jun Zhou, Chaochao Chen, Longfei Zheng, Xiaolin Zheng, Bingzhe Wu, Ziqi Liu, Li Wang

CoRR, 2020

Industrial Scale Privacy Preserving Deep Neural Network.

Longfei Zheng, Chaochao Chen, Yingting Liu, Bingzhe Wu, Xibin Wu, Li Wang, Lei Wang, Jun Zhou, Shuang Yang

CoRR, 2020

Practical Privacy Preserving POI Recommendation.

Chaochao Chen, Bingzhe Wu, Wenjin Fang, Jun Zhou, Li Wang, Yuan Qi, Xiaolin Zheng

CoRR, 2020

Automatic Knowledge Fusion in Transferrable Networks for Semantic Text Matching.

Cen Chen, Ya-Lin Zhang, Minghui Qiu, Bingzhe Wu, Li Wang, Longfei Li, Jun Zhou

Proceedings of the Companion of The 2020 Web Conference 2020, 2020

SaFace: Towards Scenario-aware Face Recognition via Edge Computing System.

Zhe Zhou, Bingzhe Wu, Zheng Liang, Guangyu Sun, Chenren Xu, Guojie Luo

Proceedings of the 3rd USENIX Workshop on Hot Topics in Edge Computing, 2020

S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search.

Zhihang Yuan, Bingzhe Wu, Guangyu Sun, Zheng Liang, Shiwan Zhao, Weichen Bi

Proceedings of the Computer Vision - ECCV 2020, 2020

Secure Social Recommendation Based on Secret Sharing.

Chaochao Chen, Liang Li, Bingzhe Wu, Cheng Hong, Li Wang, Jun Zhou

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

Nebula: A Scalable Privacy-Preserving Machine Learning System in Ant Financial.

Cen Chen, Bingzhe Wu, Li Wang, Chaochao Chen, Jin Tan, Lei Wang, Jun Zhou, Benyu Zhang

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics.

Bingzhe Wu, Chaochao Chen, Shiwan Zhao, Cen Chen, Yuan Yao, Guangyu Sun, Li Wang, Xiaolu Zhang, Jun Zhou

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

2019

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection.

Bingzhe Wu, Shiwan Zhao, Chaochao Chen, Haoyang Xu, Li Wang, Xiaolu Zhang, Guangyu Sun, Jun Zhou

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

BAYHENN: Combining Bayesian Deep Learning and Homomorphic Encryption for Secure DNN Inference.

Peichen Xie, Bingzhe Wu, Guangyu Sun

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification.

Bingzhe Wu, Shiwan Zhao, Guangyu Sun, Xiaolu Zhang, Zhong Su, Caihong Zeng, Zhihong Liu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

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

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2017

SRPGAN: Perceptual Generative Adversarial Network for Single Image Super Resolution.

Bingzhe Wu, Haodong Duan, Zhichao Liu, Guangyu Sun

CoRR, 2017

Reducing Overfitting in Deep Convolutional Neural Networks Using Redundancy Regularizer.

Bingzhe Wu, Zhichao Liu, Zhihang Yuan, Guangyu Sun, Charles Wu

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017