| Mfaba: A more faithful and accelerated boundary-based attribution method for deep neural networks Z Zhu, H Chen, J Zhang, X Wang, Z Jin, M Xue, D Zhu, KKR Choo Proceedings of the AAAI Conference on Artificial Intelligence 38 (15), 17228 …, 2024 | 24 | 2024 |
| Ge-advgan: Improving the transferability of adversarial samples by gradient editing-based adversarial generative model Z Zhu, H Chen, X Wang, J Zhang, Z Jin, KKR Choo, J Shen, D Yuan Proceedings of the 2024 SIAM international conference on data mining (SDM …, 2024 | 17 | 2024 |
| AttEXplore: Attribution for Explanation with model parameters eXploration Z Zhu, H Chen, J Zhang, X Wang, Z Jin, J Xue, FD Salim The Twelfth International Conference on Learning Representations, 2024 | 16 | 2024 |
| Enhancing transferable adversarial attacks on vision transformers through gradient normalization scaling and high-frequency adaptation Z Zhu, X Wang, Z Jin, J Zhang, H Chen The Twelfth International Conference on Learning Representations, 2024 | 15 | 2024 |
| DANAA: Towards transferable attacks with double adversarial neuron attribution Z Jin, Z Zhu, X Wang, J Zhang, J Shen, H Chen International Conference on Advanced Data Mining and Applications, 456-470, 2023 | 15 | 2023 |
| Improving adversarial transferability via frequency-based stationary point search Z Zhu, H Chen, J Zhang, X Wang, Z Jin, Q Lu, J Shen, KKR Choo Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 12 | 2023 |
| Benchmarking transferable adversarial attacks Z Jin, J Zhang, Z Zhu, H Chen arXiv preprint arXiv:2402.00418, 2024 | 11 | 2024 |
| Iterative search attribution for deep neural networks Z Zhu, H Chen, X Wang, J Zhang, Z Jin, J Xue, J Shen Forty-first International Conference on Machine Learning, 2024 | 9 | 2024 |
| Narrowing Information Bottleneck Theory for Multimodal Image-Text Representations Interpretability Z Zhu, Z Jin, J Zhang, N Yang, J Huang, J Zhou, F Chen arXiv preprint arXiv:2502.14889, 2025 | 5 | 2025 |
| Enhancing model interpretability with local attribution over global exploration Z Zhu, Z Jin, J Zhang, H Chen Proceedings of the 32nd ACM International Conference on Multimedia, 5347-5355, 2024 | 5 | 2024 |
| Rethinking transferable adversarial attacks with double adversarial neuron attribution Z Zhu, Z Jin, X Wang, J Zhang, H Chen, KKR Choo IEEE Transactions on Artificial Intelligence 6 (2), 354-364, 2024 | 5 | 2024 |
| Improving Adversarial Transferability via Frequency-Guided Sample Relevance Attack X Wang, Z Jin, Z Zhu, J Zhang, H Chen Proceedings of the 33rd ACM International Conference on Information and …, 2024 | 4 | 2024 |
| Enhancing adversarial attacks via parameter adaptive adversarial attack Z Jin, J Zhang, Z Zhu, C Zhang, J Huang, J Zhou, F Chen arXiv preprint arXiv:2408.07733, 2024 | 4 | 2024 |
| Fvw: Finding valuable weight on deep neural network for model pruning Z Zhu, H Chen, Z Jin, X Wang, J Zhang, M Xue, Q Lu, J Shen, KKR Choo Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 4 | 2023 |
| POSTER: ML-Compass: A Comprehensive Assessment Framework for Machine Learning Models Z Jin, Z Zhu, H Hu, M Xue, H Chen Proceedings of the 2023 ACM Asia Conference on Computer and Communications …, 2023 | 3 | 2023 |
| Leveraging Information Consistency in Frequency and Spatial Domain for Adversarial Attacks Z Jin, J Zhang, Z Zhu, X Wang, Y Huang, H Chen Pacific Rim International Conference on Artificial Intelligence, 93-105, 2024 | 1 | 2024 |
| AI-Compass: A Comprehensive and Effective Multi-module Testing Tool for AI Systems Z Zhu, Z Jin, H Hu, M Xue, R Sun, S Camtepe, P Gauravaram, H Chen arXiv preprint arXiv:2411.06146, 2024 | 1 | 2024 |
| Enhancing Transferability of Adversarial Attacks with GE-AdvGAN+: A Comprehensive Framework for Gradient Editing Z Jin, J Zhang, Z Zhu, C Zhang, J Huang, J Zhou, F Chen arXiv preprint arXiv:2408.12673, 2024 | 1 | 2024 |
| DMS: addressing information loss with more steps for pragmatic adversarial attacks Z Zhu, J Zhang, X Wang, Z Jin, H Chen arXiv preprint arXiv:2406.07580, 2024 | 1 | 2024 |
| Towards Minimising Perturbation Rate for Adversarial Machine Learning with Pruning Z Zhu, J Zhang, Z Jin, X Wang, M Xue, J Shen, KKR Choo, H Chen Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023 | 1 | 2023 |
