| 2026 | AAAI | Autonomous Concept Drift Threshold Determination. | Pengqian Lu, Jie Lu, Anjin Liu, En Yu, Guangquan Zhang |
| 2026 | ACL | TPA: Next Token Probability Attribution for Detecting Hallucinations in RAG. | Pengqian Lu, Jie Lu, Anjin Liu, Guangquan Zhang |
| 2025 | AAAI | Early Concept Drift Detection via Prediction Uncertainty. | Pengqian Lu, Jie Lu, Anjin Liu, Guangquan Zhang |
| 2023 | KES | TCR-M: A Topic Change Recognition-based Method for Data Stream Learning. | Kun Wang, Jie Lu, Anjin Liu, Guangquan Zhang |
| 2021 | ICML | Learning Bounds for Open-Set Learning. | Zhen Fang, Jie Lu, Anjin Liu, Feng Liu, Guangquan Zhang |
| 2020 | IJCNN | Fast Switch Nave Bayes to Avoid Redundant Update for Concept Drift Learning. | Anjin Liu, Guangquan Zhang, Kun Wang, Jie Lu |
| 2019 | IJCNN | Knowledge graph-based entity importance learning for multi-stream regression on Australian fuel price forecasting. | Dennis Chow, Anjin Liu, Guangquan Zhang, Jie Lu |
| 2017 | IJCAI | Regional Concept Drift Detection and Density Synchronized Drift Adaptation. | Anjin Liu, Yiliao Song, Guangquan Zhang, Jie Lu |
| 2014 | ICONIP | Concept Drift Detection Based on Anomaly Analysis. | Anjin Liu, Guangquan Zhang, Jie Lu |