For the most up-to-date publication list, please visit my Google Scholar profile.

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[8] Shengyao Lu, Jiuding Yang, Baochun Li, Di Niu. TreeX: Generating Global Graphical GNN Explanations via Critical Subtree Extraction. [Download]

[7] Zihan Wang, Ruichen Chen, Shengyao Lu, Ian Then, Di Niu, Xihua Wang. Machine Learning Enabled Fast Prediction of GGNMOS Performance and Inverse Design for Applications in Electrostatic Discharge, in IEEE Transactions on Electron Devices (IEEE Trans).

[6] Jiuding Yang, Shengyao Lu, Weidong Guo, Xiangyang Li, Kaitong Yang, Yu Xu, Di Niu. TaCIE: Enhancing Instruction Comprehension in Large Language Models through Task-Centred Instruction Evolution, in The 31st International Conference on Computational Linguistics (COLING 2025). [Download]

[5] Shengyao Lu, Bang Liu, Keith G. Mills, Jiao He, Di Niu. EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time, in The Forty-first International Conference on Machine Learning (ICML 2024). [Download]

[4] Shengyao Lu, Keith G. Mills, Jiao He, Bang Liu, Di Niu. GOAt: Explaining Graph Neural Networks via Graph Output Attribution, in The Twelfth International Conference on Learning Representations (ICLR 2024). [Download]

[3] Keith G. Mills, Fred X. Han, Mohammad Salameh, Shengyao Lu, Chunhua Zhou, Jiao He, Fengyu Sun, Di Niu. Building Optimal Neural Architectures using Interpretable Knowledge, in The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2024). [Download]

[2] Ruichen Chen, Shengyao Lu, Mohamed A. Elgammal, Peter Chun, Vaughn Betz, Di Niu. VPR-Gym: A Platform for Exploring AI Techniques in FPGA Placement Optimization, in The 33rd International Conference on Field-Programmable Logic and Applications (FPL 2023).

[1] Shengyao Lu$^*$, Bang Liu$^*$, Keith G. Mills, Shangling Jui, Di Niu. R5: Rule Discovery with Reinforced and Recurrent Relational Reasoning, in The Tenth International Conference on Learning Representations (ICLR 2022), Spotlight. [Download]