Synaesthesia Design Research of Motion Game in Order to Cure the White-Collar's Cervical Spondylosis. - Yuan Liu; Shiguo Li; Baisong Liu (HCI (15), 2016)

How Anthropomorphism Affects User Acceptance of a Robot Trainer in Physical Rehabilitation. - Baisong Liu; Panos Markopoulos 001; Daniel Tetteroo (HEALTHINF, 2019)

Investigating User's Preference for Anthropomorphism of a Social Robot Trainer in Physical Rehabilitation. - Baisong Liu; Panos Markopoulos 001; Daniel Tetteroo (BIOSTEC (Selected Papers), 2019)

A Novel Privacy-Preserved Recommender System Framework based on Federated Learning. - Jiangcheng Qin; Baisong Liu (CoRR, 2020)

An Explainable Person-Job Fit Model Incorporating Structured Information. - Yunchong Zhang; Baisong Liu; Jiangbo Qian; Jiangcheng Qin; Xueyuan Zhang; Xueyong Jiang (IEEE BigData, 2021)

A Novel Privacy-Preserved Recommender System Framework Based On Federated Learning. - Jiangcheng Qin; Baisong Liu; Jiangbo Qian (ICSIM, 2021)

Content-based and knowledge graph-based paper recommendation: Exploring user preferences with the knowledge graphs for scientific paper recommendation. - Hao Tang; Baisong Liu; Jiangbo Qian (Concurr. Comput. Pract. Exp., 2021)

Rethinking Mobile Interaction Design Within Service. - Zhen Xiao; Baisong Liu (HCI (41), 2022)

A Federated Multi-Server Knowledge Graph Embedding Framework For Link Prediction. - Ce Hu; Baisong Liu; Xueyuan Zhang; Zhiye Wang; Chennan Lin; Linze Luo (ICTAI, 2022)

Ranking-based Federated POI Recommendation with Geographic Effect. - Qian Dong; Baisong Liu; Xueyuan Zhang; Jiangcheng Qin; Bingyuan Wang; Jiangbo Qian (IJCNN, 2022)

FedNCF: Federated Neural Collaborative Filtering for Privacy-preserving Recommender System. - Xueyong Jiang; Baisong Liu; Jiangcheng Qin; Yunchong Zhang; Jiangbo Qian (IJCNN, 2022)

Dual-Contrastive for Federated Social Recommendation. - Linze Luo; Baisong Liu (IJCNN, 2022)

Exploring Older Adults' Acceptance, Needs, and Design Requirements towards Applying Social Robots in a Rehabilitation Context. - Baisong Liu; Daniel Tetteroo; Annick Timmermans; Panos Markopoulos 001 (RO-MAN, 2022)

Privacy-Preserving Recommendation with Debiased Obfuscaiton. - Chennan Lin; Baisong Liu; Xueyuan Zhang; Zhiye Wang; Ce Hu; Linze Luo (TrustCom, 2022)

Exploiting high-order behaviour patterns for cross-domain sequential recommendation. - Bingyuan Wang; Baisong Liu; Hao Ren; Xueyuan Zhang; Jiangcheng Qin; Qian Dong; Jiangbo Qian (Connect. Sci., 2022)

Split Two-Tower Model for Efficient and Privacy-Preserving Cross-device Federated Recommendation. - Jiangcheng Qin; Baisong Liu; Xueyuan Zhang; Jiangbo Qian (CoRR, 2022)

A Systematic Review of Experimental Work on Persuasive Social Robots. - Baisong Liu; Daniel Tetteroo; Panos Markopoulos 001 (Int. J. Soc. Robotics, 2022)

NCGAN: A neural adversarial collaborative filtering for recommender system. - Jinyang Sun; Baisong Liu; Hao Ren; Weiming Huang (J. Intell. Fuzzy Syst., 2022)

Text multi-label learning method based on label-aware attention and semantic dependency. - Baisong Liu; Xiaoling Liu; Hao Ren; Jiangbo Qian; YangYang Wang (Multim. Tools Appl., 2022)

Distracted Driver Detection Based on a CNN With Decreasing Filter Size. - Binbin Qin; Jiangbo Qian; Yu Xin; Baisong Liu; Yihong Dong (IEEE Trans. Intell. Transp. Syst., 2022)

Graph Collaborative Filtering and Data Augmentation Strategies in Dual-Target CDR. - Xiaowen Shao; Baisong Liu; Xueyuan Zhang; Junru Li; Ercong Xu; Shiqi Wu (CoopIS, 2023)

Revisiting Data Poisoning Attacks on Deep Learning Based Recommender Systems. - Zhiye Wang; Baisong Liu; Chennan Lin; Xueyuan Zhang; Ce Hu; Jiangcheng Qin; Linze Luo (ISCC, 2023)

From Research to Design: Developing the Social Robotic Persuasive Design Cards and Its Techniques. - Baisong Liu; Daniel Tetteroo; Panos Markopoulos 001 (RO-MAN, 2023)

3 Key Challenges in Designing Advanced Social Robotic Applications. - Baisong Liu; Daniel Tetteroo; Panos Markopoulos 001 (RO-MAN, 2023)

Swin transformer-based supervised hashing. - Liangkang Peng; Jiangbo Qian; Chong Wang 001; Baisong Liu; Yihong Dong (Appl. Intell., 2023)

FedPJF: federated contrastive learning for privacy-preserving person-job fit. - Yunchong Zhang; Baisong Liu; Jiangbo Qian (Appl. Intell., 2023)

A split-federated learning and edge-cloud based efficient and privacy-preserving large-scale item recommendation model. - Jiangcheng Qin; Xueyuan Zhang; Baisong Liu; Jiangbo Qian (J. Cloud Comput., 2023)

Sequential POI Recommend Based on Personalized Federated Learning. - Qian Dong; Baisong Liu; Xueyuan Zhang; Jiangcheng Qin; Bingyuan Wang (Neural Process. Lett., 2023)

Animation line art colorization based on the optical flow method. - Yifeng Yu; Jiangbo Qian; Chong Wang 001; Yihong Dong; Baisong Liu (Comput. Animat. Virtual Worlds, 2024)

Exploring the Impact of Large Language Model-Simulated Personalities on Recommendation. - Zining Feng; Zijing Wang; Hongzan Mao; Baisong Liu (CSCWD, 2025)

Federated Cross-Domain Click-Through Rate Prediction With Large Language Model Augmentation. - Jiangcheng Qin; Xueyuan Zhang; Baisong Liu; Jiangbo Qian; Yangyang Wang (CoRR, 2025)