| 2026 | SIGIR | Bridging the Gap: An End-to-End Framework for Decoupled Alignment in Dynamic Semantic ID Generation. | Yu Cheng, Wei Xu, Li Li, Jianbin Lin, Can Ye |
| 2026 | SIGIR | Generative Enhanced Modeling: A Collaborative Framework for Enhancing User Representations via Semantic ID. | Li Li, Wei Xu, Yu Cheng, Jianbin Lin, Can Ye |
| 2026 | SIGIR | SCOPE: Scalable Cross-Task Orthogonal Progressive Experts for Multi-Task Learning in Recommendations. | Zixian Yang, Wei Xu, Li Li, Zhaokai Huang, You Li, Jianbin Lin, Wenliang Zhong, Can Ye |
| 2025 | SIGIR | Towards Principled Learning for Re-ranking in Recommender Systems. | Qunwei Li, Linghui Li, Jianbin Lin, Wenliang Zhong |
| 2020 | ECAI | Generating Natural Language Adversarial Examples on a Large Scale with Generative Models. | Yankun Ren, Jianbin Lin, Siliang Tang, Jun Zhou, Shuang Yang, Yuan Qi, Xiang Ren |
| 2020 | WWW | Neural Zero-Shot Fine-Grained Entity Typing. | Yankun Ren, Jianbin Lin, Jun Zhou |
| 2019 | ICDM | A Semi-Supervised Graph Attentive Network for Financial Fraud Detection. | Daixin Wang, Yuan Qi, Jianbin Lin, Peng Cui, Quanhui Jia, Zhen Wang, Yanming Fang, Quan Yu, Jun Zhou, Shuang Yang |
| 2019 | PAKDD | RNE: A Scalable Network Embedding for Billion-Scale Recommendation. | Jianbin Lin, Daixin Wang, Lu Guan, Yin Zhao, Binqiang Zhao, Jun Zhou, Xiaolong Li, Yuan (Alan) Qi |