Jun Wang

According to our database, Jun Wang authored at least 65 papers between 2015 and 2026.

Collaborative distances:

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

2026

"I See What You Did There": Can Large Vision-Language Models Understand Multimodal Puns?

Naen Xu, Jiayi Sheng, Changjiang Li, Chunyi Zhou, Yuyuan Li, Tianyu Du, Jun Wang, Zhihui Fu, Jinbao Li, Shouling Ji

CoRR, April, 2026

Adaptive Milestone Reward for GUI Agents.

Congmin Zheng, Xiaoyun Mo, Xinbei Ma, Qiqiang Lin, Yin Zhao, Jiachen Zhu, Xingyu Lou, Jun Wang, Zhaoxiang Wang, Weiwen Liu, Zhuosheng Zhang, Yong Yu, Weinan Zhang

CoRR, February, 2026

LLM4DSR: Leveraging Large Language Model for Denoising Sequential Recommendation.

Bohao Wang, Feng Liu, Changwang Zhang, Jiawei Chen, Yudi Wu, Sheng Zhou, Xingyu Lou, Jun Wang, Yan Feng, Chun Chen, Can Wang

ACM Trans. Inf. Syst., January, 2026

SpecTran: Spectral-Aware Transformer-based Adapter for LLM-Enhanced Sequential Recommendation.

Yu Cui, Feng Liu, Zhaoxiang Wang, Changwang Zhang, Jun Wang, Can Wang, Jiawei Chen

CoRR, January, 2026

Sharpness-Aware Minimization for Generalized Embedding Learning in Federated Recommendation.

Fengyuan Yu, Xiaohua Feng, Yuyuan Li, Changwang Zhang, Jun Wang, Chaochao Chen

Proceedings of the ACM Web Conference 2026, 2026

FraudShield: Knowledge Graph Empowered Defense for LLMs against Fraud Attacks.

Naen Xu, Jinghuai Zhang, Ping He, Chunyi Zhou, Jun Wang, Zhihui Fu, Tianyu Du, Zhaoxiang Wang, Shouling Ji

Proceedings of the ACM Web Conference 2026, 2026

Does LLM Focus on the Right Words? Mitigating Context Bias in LLM-based Recommenders.

Bohao Wang, Jiawei Chen, Feng Liu, Changwang Zhang, Jun Wang, Canghong Jin, Chun Chen, Can Wang

Proceedings of the ACM Web Conference 2026, 2026

ColorBench: Benchmarking Mobile Agents with Graph-Structured Framework for Complex Long-Horizon Tasks.

Yuanyi Song, Heyuan Huang, Qiqiang Lin, Yin Zhao, Xiangmou Qu, Jun Wang, Xingyu Lou, Weiwen Liu, Zhuosheng Zhang, Jun Wang, Zhaoxiang Wang, Yong Yu, Weinan Zhang

Proceedings of the ACM Web Conference 2026, 2026

Field Matters: A Lightweight LLM-enhanced Method for CTR Prediction.

Yu Cui, Feng Liu, Jiawei Chen, Xingyu Lou, Changwang Zhang, Jun Wang, Yuegang Sun, Xiaohu Yang, Can Wang

Proceedings of the ACM Web Conference 2026, 2026

2025

Does LLM Focus on the Right Words? Diagnosing Language Bias in LLM-based Recommenders.

Bohao Wang, Jiawei Chen, Feng Liu, Changwang Zhang, Jun Wang, Canghong Jin, Chun Chen, Can Wang

CoRR, October, 2025

HatLLM: Hierarchical Attention Masking for Enhanced Collaborative Modeling in LLM-based Recommendation.

Yu Cui, Feng Liu, Jiawei Chen, Canghong Jin, Xingyu Lou, Changwang Zhang, Jun Wang, Yuegang Sun, Can Wang

CoRR, October, 2025

Open Source AI-based SE Tools: Opportunities and Challenges of Collaborative Software Learning.

Zhihao Lin, Wei Ma, Tao Lin, Yaowen Zheng, Jingquan Ge, Jun Wang, Jacques Klein, Tegawendé F. Bissyandé, Yang Liu, Li Li

ACM Trans. Softw. Eng. Methodol., June, 2025

OThink-R1: Intrinsic Fast/Slow Thinking Mode Switching for Over-Reasoning Mitigation.

Shengjia Zhang, Junjie Wu, Jiawei Chen, Changwang Zhang, Xingyu Lou, Wangchunshu Zhou, Sheng Zhou, Can Wang, Jun Wang

CoRR, June, 2025

Post-Training Attribute Unlearning in Recommender Systems.

Chaochao Chen, Yizhao Zhang, Yuyuan Li, Jun Wang, Lianyong Qi, Xiaolong Xu, Xiaolin Zheng, Jianwei Yin

ACM Trans. Inf. Syst., January, 2025

ADSS: An Available-but-Invisible Data Service Scheme for Fine-Grained Usage Control.

Hao Wang, Jun Wang, Chunpeng Ge, Yuhang Li, Lu Zhou, Zhe Liu, Weibin Wu, Mingsheng Cao

IEEE Trans. Serv. Comput., 2025

Joint Similarity Item Exploration and Overlapped User Guidance for Multi-Modal Cross-Domain Recommendation.

Weiming Liu, Chaochao Chen, Jiahe Xu, Xinting Liao, Fan Wang, Xiaolin Zheng, Zhihui Fu, Ruiguang Pei, Jun Wang

Proceedings of the ACM on Web Conference 2025, 2025

FedGF: Enhancing Structural Knowledge via Graph Factorization for Federated Graph Learning.

Pengyang Zhou, Chaochao Chen, Weiming Liu, Xinting Liao, Fengyuan Yu, Zhihui Fu, Xingyu Lou, Wu Wen, Xiaolin Zheng, Jun Wang

Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining, 2025

HapRepair: Learn to Repair OpenHarmony Apps.

Zhihao Lin, Mingyi Zhou, Wei Ma, Chi Chen, Yun Yang, Jun Wang, Chunming Hu, Li Li

Proceedings of the 33rd ACM International Conference on the Foundations of Software Engineering, 2025

Joint Item Embedding Dual-view Exploration and Adaptive Local-Global Fusion for Federated Recommendation.

Pengyang Zhou, Chaochao Chen, Weiming Liu, Wenkai Shen, Xinting Liao, Huarong Deng, Zhihui Fu, Jun Wang, Wu Wen, Xiaolin Zheng

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

MSL: Not All Tokens Are What You Need for Tuning LLM as a Recommender.

Bohao Wang, Feng Liu, Jiawei Chen, Xingyu Lou, Changwang Zhang, Jun Wang, Yuegang Sun, Yan Feng, Chun Chen, Can Wang

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

Training-free Periodic Interest Augmentation in Incremental Recommendation.

Heyuan Huang, Xingyu Lou, Changwang Zhang, Chaochao Chen, Kuiyao Dong, Feng Lu, Han Lei, Yihao Wang, Wangchunshu Zhou, Jun Wang

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

Diversity-Aware Self-Paced Data Selection for LLM Fine-Tuning.

Yingxuan Yang, Huayi Wang, Muning Wen, Xiaoyun Mo, Qiuying Peng, Jun Wang, Weinan Zhang

Proceedings of the ECAI 2025 - 28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy, 2025

Personalized Federated Recommendation with Multi-Faceted User Representation and Global Consistent Prototype.

Jiaming Qian, Xinting Liao, Xiangmou Qu, Zhihui Fu, Xingyu Lou, Changwang Zhang, Pengyang Zhou, Zijun Zhou, Jun Wang, Chaochao Chen

Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025

HammerBench: Fine-Grained Function-Calling Evaluation in Real Mobile Assistant Scenarios.

Jun Wang, Jiamu Zhou, Xihuai Wang, Xiaoyun Mo, Haoyu Zhang, Qiqiang Lin, Jincheng Jincheng, Muning Wen, Weinan Zhang, Qiuying Peng

Proceedings of the Findings of the Association for Computational Linguistics, 2025

FedGOG: Federated Graph Out-of-Distribution Generalization with Diffusion Data Exploration and Latent Embedding Decorrelation.

Pengyang Zhou, Chaochao Chen, Weiming Liu, Xinting Liao, Wenkai Shen, Jiahe Xu, Zhihui Fu, Jun Wang, Wu Wen, Xiaolin Zheng

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

Sim4Rec: Data-Free Model Extraction Attack on Sequential Recommendation.

Yihao Wang, Jiajie Su, Chaochao Chen, Meng Han, Chi Zhang, Jun Wang

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Making recommender systems forget: Learning and unlearning for erasable recommendation.

Yuyuan Li, Chaochao Chen, Xiaolin Zheng, Junlin Liu, Jun Wang

Knowl. Based Syst., January, 2024

Voltran: Unlocking Trust and Confidentiality in Decentralized Federated Learning Aggregation.

Hao Wang, Yichen Cai, Jun Wang, Chuan Ma, Chunpeng Ge, Xiangmou Qu, Lu Zhou

IEEE Trans. Inf. Forensics Secur., 2024

HammerBench: Fine-Grained Function-Calling Evaluation in Real Mobile Device Scenarios.

Jun Wang, Jiamu Zhou, Muning Wen, Xiaoyun Mo, Haoyu Zhang, Qiqiang Lin, Cheng Jin, Xihuai Wang, Weinan Zhang, Qiuying Peng, Jun Wang

CoRR, 2024

Adaptive Conditional Expert Selection Network for Multi-domain Recommendation.

Kuiyao Dong, Xingyu Lou, Feng Liu, Ruian Wang, Wenyi Yu, Ping Wang, Jun Wang

CoRR, 2024

Hammer: Robust Function-Calling for On-Device Language Models via Function Masking.

Qiqiang Lin, Muning Wen, Qiuying Peng, Guanyu Nie, Junwei Liao, Jun Wang, Xiaoyun Mo, Jiamu Zhou, Cheng Cheng, Yin Zhao, Jun Wang, Weinan Zhang

CoRR, 2024

PathSeeker: Exploring LLM Security Vulnerabilities with a Reinforcement Learning-Based Jailbreak Approach.

Zhihao Lin, Wei Ma, Mingyi Zhou, Yanjie Zhao, Haoyu Wang, Yang Liu, Jun Wang, Li Li

CoRR, 2024

LLM4DSR: Leveraing Large Language Model for Denoising Sequential Recommendation.

Bohao Wang, Feng Liu, Jiawei Chen, Yudi Wu, Xingyu Lou, Jun Wang, Yan Feng, Chun Chen, Can Wang

CoRR, 2024

Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language Model.

Yu Cui, Feng Liu, Pengbo Wang, Bohao Wang, Heng Tang, Yi Wan, Jun Wang, Jiawei Chen

CoRR, 2024

Post-Training Attribute Unlearning in Recommender Systems.

Chaochao Chen, Yizhao Zhang, Yuyuan Li, Dan Meng, Jun Wang, Xiaoli Zheng, Jianwei Yin

CoRR, 2024

A Framework to Implement 1+N Multi-task Fine-tuning Pattern in LLMs Using the CGC-LORA Algorithm.

Chao Song, Zhihao Ye, Qiqiang Lin, Qiuying Peng, Jun Wang

CoRR, 2024

Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language Models.

Yu Cui, Feng Liu, Pengbo Wang, Bohao Wang, Heng Tang, Yi Wan, Jun Wang, Jiawei Chen

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection.

Xinting Liao, Weiming Liu, Pengyang Zhou, Fengyuan Yu, Jiahe Xu, Jun Wang, Wenjie Wang, Chaochao Chen, Xiaolin Zheng

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

GlitchProber: Advancing Effective Detection and Mitigation of Glitch Tokens in Large Language Models.

Zhibo Zhang, Wuxia Bai, Yuxi Li, Mark Huasong Meng, Kailong Wang, Ling Shi, Li Li, Jun Wang, Haoyu Wang

Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering, 2024

DIIT: A Domain-Invariant Information Transfer Method for Industrial Cross-Domain Recommendation.

Heyuan Huang, Xingyu Lou, Chaochao Chen, Pengxiang Cheng, Yue Xin, Chengwei He, Xiang Liu, Jun Wang

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Selective and collaborative influence function for efficient recommendation unlearning.

Yuyuan Li, Chaochao Chen, Xiaolin Zheng, Yizhao Zhang, Biao Gong, Jun Wang, Linxun Chen

Expert Syst. Appl., December, 2023

VPiP: Values Packing in Paillier for Communication Efficient Oblivious Linear Computations.

Weibin Wu, Jun Wang, Yangpan Zhang, Zhe Liu, Lu Zhou, Xiaodong Lin

IEEE Trans. Inf. Forensics Secur., 2023

Selective and Collaborative Influence Function for Efficient Recommendation Unlearning.

Yuyuan Li, Chaochao Chen, Xiaolin Zheng, Yizhao Zhang, Biao Gong, Jun Wang

CoRR, 2023

UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition.

Yuyuan Li, Chaochao Chen, Yizhao Zhang, Weiming Liu, Lingjuan Lyu, Xiaolin Zheng, Dan Meng, Jun Wang

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

Differentially Private Sparse Mapping for Privacy-Preserving Cross Domain Recommendation.

Weiming Liu, Xiaolin Zheng, Chaochao Chen, Mengling Hu, Xinting Liao, Fan Wang, Yanchao Tan, Dan Meng, Jun Wang

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Making Users Indistinguishable: Attribute-wise Unlearning in Recommender Systems.

Yuyuan Li, Chaochao Chen, Xiaolin Zheng, Yizhao Zhang, Zhongxuan Han, Dan Meng, Jun Wang

Proceedings of the 31st ACM International Conference on Multimedia, 2023

In-processing User Constrained Dominant Sets for User-Oriented Fairness in Recommender Systems.

Zhongxuan Han, Chaochao Chen, Xiaolin Zheng, Weiming Liu, Jun Wang, Wenjie Cheng, Yuyuan Li

Proceedings of the 31st ACM International Conference on Multimedia, 2023

HyperFed: Hyperbolic Prototypes Exploration with Consistent Aggregation for Non-IID Data in Federated Learning.

Xinting Liao, Weiming Liu, Chaochao Chen, Pengyang Zhou, Huabin Zhu, Yanchao Tan, Jun Wang, Yue Qi

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

FedLRS: A Communication-Efficient Federated Learning Framework With Low-Rank and Sparse Decomposition.

Mingkai Luo, Dan Meng, Jun Wang, Yu Fang, Jiangyong Ying

Proceedings of the 29th IEEE International Conference on Parallel and Distributed Systems, 2023

Backdoor Attack Against Automatic Speaker Verification Models in Federated Learning.

Dan Meng, Xue Wang, Jun Wang

Proceedings of the IEEE International Conference on Acoustics, 2023

FedPerturb: Covert Poisoning Attack on Federated Learning via Partial Perturbation.

Tongsai Jin, Zhihui Fu, Dan Meng, Jun Wang, Yue Qi, Guitao Cao

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2022

CryptoRec: Novel Collaborative Filtering Recommender Made Privacy-Preserving Easy.

Jun Wang, Chao Jin, Qiang Tang, Zhe Liu, Khin Mi Mi Aung

IEEE Trans. Dependable Secur. Comput., 2022

2021

Recommendation Fairness: From Static to Dynamic.

Dell Zhang, Jun Wang

CoRR, 2021

Popcorn: Paillier Meets Compression For Efficient Oblivious Neural Network Inference.

Jun Wang, Chao Jin, Souhail Meftah, Khin Mi Mi Aung

CoRR, 2021

Automatic test suite generation for key-points detection DNNs using many-objective search (experience paper).

Fitash Ul Haq, Donghwan Shin, Lionel C. Briand, Thomas Stifter, Jun Wang

Proceedings of the ISSTA '21: 30th ACM SIGSOFT International Symposium on Software Testing and Analysis, 2021

2020

Automatic Test Suite Generation for Key-points Detection DNNs Using Many-Objective Search.

Fitash Ul Haq, Donghwan Shin, Lionel C. Briand, Thomas Stifter, Jun Wang

CoRR, 2020

2019

Novel Collaborative Filtering Recommender Friendly to Privacy Protection.

Jun Wang, Qiang Tang, Afonso Arriaga, Peter Y. A. Ryan

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

2018

Privacy-preserving Recommender Systems Facilitated By The Machine Learning Approach.

Jun Wang

PhD thesis, 2018

Privacy-Preserving Friendship-Based Recommender Systems.

Qiang Tang, Jun Wang

IEEE Trans. Dependable Secur. Comput., 2018

CryptoRec: Secure Recommendations as a Service.

Jun Wang, Afonso Arriaga, Qiang Tang, Peter Y. A. Ryan

CoRR, 2018

Facilitating Privacy-preserving Recommendation-as-a-Service with Machine Learning.

Jun Wang, Afonso Arriaga, Qiang Tang, Peter Y. A. Ryan

Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, 2018

2017

Differentially Private Neighborhood-Based Recommender Systems.

Jun Wang, Qiang Tang

Proceedings of the ICT Systems Security and Privacy Protection, 2017

2016

A Probabilistic View of Neighborhood-Based Recommendation Methods.

Jun Wang, Qiang Tang

Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

2015

Recommender Systems and their Security Concerns.

Jun Wang, Qiang Tang

IACR Cryptol. ePrint Arch., 2015

Privacy-Preserving Context-Aware Recommender Systems: Analysis and New Solutions.

Qiang Tang, Jun Wang

Proceedings of the Computer Security - ESORICS 2015, 2015