A Truthful Procurement Auction for Incentivizing Heterogeneous Clients in Federated Learning. - Ruiting Zhou; Jinlong Pang; Zhibo Wang 001; John C. S. Lui; Zongpeng Li (ICDCS, 2021)

Online Scheduling Unbiased Distributed Learning over Wireless Edge Networks. - Ziyi Han; Ruiting Zhou; Jinlong Pang; Yue Cao 002; Haisheng Tan (ICPADS, 2021)

Curvature Continuous Path Planning with Reverse Searching for Efficient and Precise Autonomous Parking. - Jinlong Pang; Songyi Zhang; Jiawei Fu 001; Jianyi Liu; Nanning Zheng 001 (ITSC, 2022)

Online scheduling algorithms for unbiased distributed learning over wireless edge networks. - Jinlong Pang; Ziyi Han; Ruiting Zhou; Haisheng Tan; Yue Cao 002 (J. Syst. Archit., 2022)

Multi-risk Aware Trajectory Planning for Car-like Robot in Highly Dynamic Environments. - Ming Chen; Jianyi Liu; Jinlong Pang; Zhiqiang Jian; Pei Chen; Xinhu Zheng (ITSC, 2023)

DVT-Tree: Dynamic Visible Topology Tree for Efficient Mapless Navigation in Maze Environments. - Yucong Zhong; Jianyi Liu; Zhiqiang Jian; Jinlong Pang; Shitao Chen; Xinhu Zheng (ITSC, 2023)

Online Scheduling Algorithm for Heterogeneous Distributed Machine Learning Jobs. - Ruiting Zhou; Jinlong Pang; Qin Zhang; Chuan Wu 001; Lei Jiao 002; Yi Zhong; Zongpeng Li (IEEE Trans. Cloud Comput., 2023)

An Incentive Auction for Heterogeneous Client Selection in Federated Learning. - Jinlong Pang; Jieling Yu; Ruiting Zhou; John C. S. Lui (IEEE Trans. Mob. Comput., 2023)

DPS: Dynamic Pricing and Scheduling for Distributed Machine Learning Jobs in Edge-Cloud Networks. - Ruiting Zhou; Ne Wang; Yifeng Huang; Jinlong Pang; Hao Chen (IEEE Trans. Mob. Comput., 2023)

Towards Practical Overlay Networks for Decentralized Federated Learning. - Yifan Hua; Jinlong Pang; Xiaoxue Zhang 001; Yi Liu 069; Xiaofeng Shi; Bao Wang; Yang Liu 003; Chen Qian 001 (ICNP, 2024)

Fairness without Harm: An Influence-Guided Active Sampling Approach. - Jinlong Pang; Jialu Wang; Zhaowei Zhu; Yuanshun Yao; Chen Qian 001; Yang Liu 018 (NeurIPS, 2024)

Fair Classifiers Without Fair Training: An Influence-Guided Data Sampling Approach. - Jinlong Pang; Jialu Wang; Zhaowei Zhu; Yuanshun Yao; Chen Qian 001; Yang Liu 018 (CoRR, 2024)

Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond. - Minghao Liu 009; Zonglin Di; Jiaheng Wei; Zhongruo Wang; Hengxiang Zhang; Ruixuan Xiao; Haoyu Wang 001; Jinlong Pang; Hao Chen 102; Ankit Shah 001; Hongxin Wei; Xinlei He 001; et al. (CoRR, 2024)

Improving Data Efficiency via Curating LLM-Driven Rating Systems. - Jinlong Pang; Jiaheng Wei; Ankit Parag Shah; Zhaowei Zhu; Yaxuan Wang; Chen Qian 001; Yang Liu 018; Yujia Bao; Wei Wei 019 (CoRR, 2024)

LLM Unlearning via Loss Adjustment with Only Forget Data. - Yaxuan Wang; Jiaheng Wei; Chris Yuhao Liu; Jinlong Pang; Quan Liu; Ankit Parag Shah; Yujia Bao; Yang Liu 018; Wei Wei 019 (CoRR, 2024)

Eris: An Online Auction for Scheduling Unbiased Distributed Learning Over Edge Networks. - Jinlong Pang; Ziyi Han; Ruiting Zhou; Renli Zhang; John C. S. Lui; Hao Chen (IEEE Trans. Mob. Comput., 2024)

Improving Data Efficiency via Curating LLM-Driven Rating Systems. - Jinlong Pang; Jiaheng Wei; Ankit Shah 001; Zhaowei Zhu; Yaxuan Wang; Chen Qian 001; Yang Liu 018; Yujia Bao; Wei Wei 019 (ICLR, 2025)

LLM Unlearning via Loss Adjustment with Only Forget Data. - Yaxuan Wang; Jiaheng Wei; Chris Yuhao Liu; Jinlong Pang; Quan Liu; Ankit Shah 001; Yujia Bao; Yang Liu 018; Wei Wei 019 (ICLR, 2025)

Token Cleaning: Fine-Grained Data Selection for LLM Supervised Fine-Tuning. - Jinlong Pang; Na Di; Zhaowei Zhu; Jiaheng Wei; Hao Cheng; Chen Qian 001; Yang Liu (CoRR, 2025)

Evaluating LLM-corrupted Crowdsourcing Data Without Ground Truth. - Yichi Zhang; Jinlong Pang; Zhaowei Zhu; Yang Liu (CoRR, 2025)

Incentivizing High-quality Participation From Federated Learning Agents. - Jinlong Pang; Jiaheng Wei; Yifan Hua; Chen Qian 001; Yang Liu 018 (CoRR, 2025)