| 2026 | AAAI | Breaking the Passive Learning Trap: An Active Perception Strategy for Human Motion Prediction. | Juncheng Hu, Zijian Zhang, Zeyu Wang, Guoyu Wang, Yingji Li, Kedi Lyu |
| 2026 | ACL | Distilling the Essence, Discarding the Dross: Improving Fairness in Multimodal Large Language Models via Historical Reflection-Guided Prompt Optimization. | Juncheng Hu, Jiming Yu, Rui Song, Kedi Lyu, Yingji Li, Zheli Liu |
| 2026 | ACL | From Fake to Real: Mitigating Out-of-Distribution Bias in In-Context Learning via Feedback Supervision from Large Language Models. | Rui Song, Yingji Li, Jian Li, Fausto Giunchiglia, Hao Xu |
| 2026 | ACL | Enhancing Multimodal Large Language Models for Ancient Chinese Character Evolution Analysis via Glyph-Driven Fine-Tuning. | Rui Song, Lida Shi, Ruihua Qi, Yingji Li, Hao Xu |
| 2026 | ACL | Toward Robust In-Context Learning: Leveraging Out-of-distribution Proxies for Target Inaccessible Demonstration Retrieval. | Hao Xu, Rite Bo, Fausto Giunchiglia, Yingji Li, Rui Song |
| 2025 | KDD | Generalizable Graph Prompt Learning Framework with Model-level Prompt Injection and Two-Stage Prompt Tuning. | Mingchen Sun, Jiahui Hou, Yutong Zhang, Yingji Li, Ying Wang |
| 2024 | AAAI | TACIT: A Target-Agnostic Feature Disentanglement Framework for Cross-Domain Text Classification. | Rui Song, Fausto Giunchiglia, Yingji Li, Mingjie Tian, Hao Xu |
| 2024 | ACL | Data-Centric Explainable Debiasing for Improving Fairness in Pre-trained Language Models. | Yingji Li, Mengnan Du, Rui Song, Xin Wang, Ying Wang |
| 2023 | ACL | Prompt Tuning Pushes Farther, Contrastive Learning Pulls Closer: A Two-Stage Approach to Mitigate Social Biases. | Yingji Li, Mengnan Du, Xin Wang, Ying Wang |