| 2026 | ACL | PerfCoder: Large Language Models for Interpretable Code Performance Optimization. | Jiuding Yang, Shengyao Lu, Hongxuan Liu, Shayan Shirahmad Gale Bagi, Zahra Fazel, Tomasz Czajkowski, Di Niu |
| 2025 | COLING | TaCIE: Enhancing Instruction Comprehension in Large Language Models through Task-Centred Instruction Evolution. | Jiuding Yang, Shengyao Lu, Weidong Guo, Xiangyang Li, Kaitong Yang, Yu Xu, Di Niu |
| 2024 | CVPR | Building Optimal Neural Architectures Using Interpretable Knowledge. | Keith G. Mills, Fred X. Han, Mohammad Salameh, Shengyao Lu, Chunhua Zhou, Jiao He, Fengyu Sun, Di Niu |
| 2024 | ICLR | GOAt: Explaining Graph Neural Networks via Graph Output Attribution. | Shengyao Lu, Keith G. Mills, Jiao He, Bang Liu, Di Niu |
| 2024 | ICML | EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time. | Shengyao Lu, Bang Liu, Keith G. Mills, Jiao He, Di Niu |
| 2023 | FPL | VPR-Gym: A Platform for Exploring AI Techniques in FPGA Placement Optimization. | Ruichen Chen, Shengyao Lu, Mohamed A. Elgammal, Peter Chun, Vaughn Betz, Di Niu |
| 2022 | ICLR | R5: Rule Discovery with Reinforced and Recurrent Relational Reasoning. | Shengyao Lu, Bang Liu, Keith G. Mills, Shangling Jui, Di Niu |