PBPAFL: A Federated Learning Framework with Hybrid Privacy Protection for Sensitive Data. - Ruichu Yao; Kunsheng Tang; Yongshi Zhu; Bingbing Fan; Tian Luo; Yide Song (ICDF2C, 2022)

FunctionMarker: Watermarking Language Datasets via Knowledge Injection. - Shuai Li; Kejiang Chen; Kunsheng Tang; Wen Huang; Jie Zhang 073; Weiming Zhang 001; Nenghai Yu (CoRR, 2023)

Control Risk for Potential Misuse of Artificial Intelligence in Science. - Jiyan He; Weitao Feng 001; Yaosen Min; Jingwei Yi; Kunsheng Tang; Shuai Li; Jie Zhang 073; Kejiang Chen; Wenbo Zhou; Xing Xie 001; Weiming Zhang 001; Nenghai Yu; et al. (CoRR, 2023)

Reconciling privacy and utility: an unscented Kalman filter-based framework for differentially private machine learning. - Kunsheng Tang; Ping Li 018; Yide Song; Tian Luo (Mach. Learn., 2023)

GenderCARE: A Comprehensive Framework for Assessing and Reducing Gender Bias in Large Language Models. - Kunsheng Tang; Wenbo Zhou; Jie Zhang 073; Aishan Liu; Gelei Deng; Shuai Li; Peigui Qi; Weiming Zhang 001; Tianwei Zhang 004; Nenghai Yu (CCS, 2024)

FinRipple: Aligning Large Language Models with Financial Market for Event Ripple Effect Awareness. - Yuanjian Xu; Jianing Hao; Kunsheng Tang; Jingnan Chen; Anxian Liu; Peng Liu; Guang Zhang (ACL (Findings), 2025)

PoseGuard: Pose-Guided Generation with Safety Guardrails. - Kongxin Wang; Jie Zhang 073; Peigui Qi; Kunsheng Tang; Tianwei Zhang 004; Wenbo Zhou (CoRR, 2025)