| Deephunter: a coverage-guided fuzz testing framework for deep neural networks X Xie, L Ma, F Juefei-Xu, M Xue, H Chen, Y Liu, J Zhao, B Li, J Yin, S See Proceedings of the 28th ACM SIGSOFT international symposium on software …, 2019 | 510* | 2019 |
| Hawkeye: Towards a desired directed grey-box fuzzer H Chen, Y Xue, Y Li, B Chen, X Xie, X Wu, Y Liu Proceedings of the 2018 ACM SIGSAC conference on computer and communications …, 2018 | 302 | 2018 |
| Fakespotter: A simple yet robust baseline for spotting ai-synthesized fake faces R Wang, F Juefei-Xu, L Ma, X Xie, Y Huang, J Wang, Y Liu arXiv preprint arXiv:1909.06122, 2019 | 290 | 2019 |
| Deeprhythm: Exposing deepfakes with attentional visual heartbeat rhythms H Qi, Q Guo, F Juefei-Xu, X Xie, L Ma, W Feng, Y Liu, J Zhao Proceedings of the 28th ACM international conference on multimedia, 4318-4327, 2020 | 224 | 2020 |
| Deepstellar: Model-based quantitative analysis of stateful deep learning systems X Du, X Xie, Y Li, L Ma, Y Liu, J Zhao Proceedings of the 2019 27th ACM Joint Meeting on European Software …, 2019 | 209* | 2019 |
| Wuji: Automatic online combat game testing using evolutionary deep reinforcement learning Y Zheng, X Xie, T Su, L Ma, J Hao, Z Meng, Y Liu, R Shen, Y Chen, C Fan 2019 34th IEEE/ACM International Conference on Automated Software …, 2019 | 170 | 2019 |
| Retrieval-augmented generation for code summarization via hybrid gnn S Liu, Y Chen, X Xie, J Siow, Y Liu arXiv preprint arXiv:2006.05405, 2020 | 163 | 2020 |
| An empirical study towards characterizing deep learning development and deployment across different frameworks and platforms Q Guo, S Chen, X Xie, L Ma, Q Hu, H Liu, Y Liu, J Zhao, X Li 2019 34th IEEE/ACM International Conference on Automated Software …, 2019 | 134 | 2019 |
| Memlock: Memory usage guided fuzzing C Wen, H Wang, Y Li, S Qin, Y Liu, Z Xu, H Chen, X Xie, G Pu, T Liu Proceedings of the ACM/IEEE 42nd International Conference on Software …, 2020 | 132 | 2020 |
| Stealthy and efficient adversarial attacks against deep reinforcement learning J Sun, T Zhang, X Xie, L Ma, Y Zheng, K Chen, Y Liu Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5883-5891, 2020 | 124 | 2020 |
| A performance-sensitive malware detection system using deep learning on mobile devices R Feng, S Chen, X Xie, G Meng, SW Lin, Y Liu IEEE Transactions on Information Forensics and Security 16, 1563-1578, 2020 | 122 | 2020 |
| Deepmutation++: A mutation testing framework for deep learning systems Q Hu, L Ma, X Xie, B Yu, Y Liu, J Zhao 2019 34th IEEE/ACM International Conference on Automated Software …, 2019 | 119 | 2019 |
| Typestate-guided fuzzer for discovering use-after-free vulnerabilities H Wang, X Xie, Y Li, C Wen, Y Li, Y Liu, S Qin, H Chen, Y Sui Proceedings of the ACM/IEEE 42nd International Conference on Software …, 2020 | 113 | 2020 |
| Deepsonar: Towards effective and robust detection of ai-synthesized fake voices R Wang, F Juefei-Xu, Y Huang, Q Guo, X Xie, L Ma, Y Liu Proceedings of the 28th ACM international conference on multimedia, 1207-1216, 2020 | 111 | 2020 |
| Efficientderain: Learning pixel-wise dilation filtering for high-efficiency single-image deraining Q Guo, J Sun, F Juefei-Xu, L Ma, X Xie, W Feng, Y Liu, J Zhao Proceedings of the AAAI Conference on Artificial Intelligence 35 (2), 1487-1495, 2021 | 104 | 2021 |
| Spark: Spatial-aware online incremental attack against visual tracking Q Guo, X Xie, F Juefei-Xu, L Ma, Z Li, W Xue, W Feng, Y Liu European conference on computer vision, 202-219, 2020 | 97 | 2020 |
| Cerebro: context-aware adaptive fuzzing for effective vulnerability detection Y Li, Y Xue, H Chen, X Wu, C Zhang, X Xie, H Wang, Y Liu Proceedings of the 2019 27th ACM Joint Meeting on European Software …, 2019 | 94 | 2019 |
| Audee: Automated testing for deep learning frameworks Q Guo, X Xie, Y Li, X Zhang, Y Liu, X Li, C Shen Proceedings of the 35th IEEE/ACM international conference on automated …, 2020 | 90 | 2020 |
| Diffchaser: Detecting disagreements for deep neural networks X Xie, L Ma, H Wang, Y Li, Y Liu, X Li International Joint Conferences on Artificial Intelligence Organization, 2019 | 88 | 2019 |
| Towards characterizing adversarial defects of deep learning software from the lens of uncertainty X Zhang, X Xie, L Ma, X Du, Q Hu, Y Liu, J Zhao, M Sun Proceedings of the ACM/IEEE 42nd International Conference on Software …, 2020 | 87 | 2020 |
Yang LiuNanyang Technological UniversityBestätigte E-Mail-Adresse bei ntu.edu.sg
