| Structural coverage criteria for neural networks could be misleading Z Li, X Ma, C Xu, C Cao International Conference on Software Engineering: New Ideas and Emerging …, 2019 | 133 | 2019 |
| Boosting operational dnn testing efficiency through conditioning Z Li, X Ma, C Xu, C Cao, J Xu, J Lü ACM Joint Meeting on European Software Engineering Conference and Symposium …, 2019 | 103 | 2019 |
| Operational calibration: Debugging confidence errors for dnns in the field Z Li, X Ma, C Xu, J Xu, C Cao, J Lü ACM Joint Meeting on European Software Engineering Conference and Symposium …, 2020 | 30 | 2020 |
| Fair representation learning: An alternative to mutual information J Liu, Z Li, Y Yao, F Xu, X Ma, M Xu, H Tong ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022 | 25 | 2022 |
| Softened symbol grounding for neuro-symbolic systems Z Li, Y Yao, T Chen, J Xu, C Cao, X Ma, J Lü International Conference on Learning Representations (ICLR), 2023 | 18 | 2023 |
| Learning with logical constraints but without shortcut satisfaction Z Li, Z Liu, Y Yao, J Xu, T Chen, X Ma, J Lü International Conference on Learning Representations (ICLR), 2023 | 17 | 2023 |
| Towards effective metamorphic testing by algorithm stability for linear classification programs Y Yang, Z Li, H Wang, C Xu, X Ma Journal of Systems and Software (JSS) 180, 111012, 2021 | 8 | 2021 |
| Predicted robustness as qos for deep neural network models YH Wang, ZN Li, JW Xu, P Yu, T Chen, XX Ma Journal of Computer Science and Technology (JCST) 35, 999-1015, 2020 | 7 | 2020 |
| A deep learning dataloader with shared data preparation J Xu, G Wang, Y Yao, Z Li, C Cao, H Tong Advances in Neural Information Processing Systems (NeurIPS), 2022 | 6 | 2022 |
| Fast robustness prediction for deep neural network Y Wang, Z Li, J Xu, P Yu, X Ma Proceedings of the 11th Asia-Pacific Symposium on Internetware, 1-10, 2019 | 5 | 2019 |
| Neuro-symbolic learning yielding logical constraints Z Li, Y Huang, Z Li, Y Yao, J Xu, T Chen, X Ma, J Lu Advances in Neural Information Processing Systems (NeurIPS), 2023 | 4 | 2023 |
| On the Vulnerability of Graph Learning-based Collaborative Filtering S Xu, L Li, Z Li, Y Yao, F Xu, Z Chen, Q Lu, H Tong ACM Transactions on Information Systems (ToIS) 41 (4), 1-28, 2023 | 3 | 2023 |
| A Survey on Deep Learning for Theorem Proving Z Li, J Sun, L Murphy, Q Su, Z Li, X Zhang, K Yang, X Si Conference on Language Modeling (COLM), 2024 | 2 | 2024 |
| Lightweight Approaches to DNN Regression Error Reduction: An Uncertainty Alignment Perspective Z Li, M Zhang, J Xu, Y Yao, C Cao, T Chen, X Ma, J Lü International Conference on Software Engineering (ICSE), 2023 | 1 | 2023 |
| Neuro-Symbolic Data Generation for Math Reasoning Z Li, Z Zhou, Y Yao, X Zhang, YF Li, C Cao, F Yang, X Ma Advances in Neural Information Processing Systems (NeurIPS), 2024 | | 2024 |
| Autoformalize Mathematical Statements by Symbolic Equivalence and Semantic Consistency Z Li, Y Wu, Z Li, X Wei, X Zhang, F Yang, X Ma Advances in Neural Information Processing Systems (NeurIPS), 2024 | | 2024 |
