| DVERGE: diversifying vulnerabilities for enhanced robust generation of ensembles H Yang, J Zhang, H Dong, N Inkawhich, A Gardner, A Touchet, W Wilkes, ... Advances in Neural Information Processing Systems (NeurIPS), 2020 | 119 | 2020 |
| Openood v1. 5: Enhanced benchmark for out-of-distribution detection J Zhang, J Yang, P Wang, H Wang, Y Lin, H Zhang, Y Sun, X Du, K Zhou, ... arXiv preprint arXiv:2306.09301, 2023 | 51 | 2023 |
| Mixture outlier exposure: Towards out-of-distribution detection in fine-grained environments J Zhang, N Inkawhich, R Linderman, Y Chen, H Li Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 47* | 2023 |
| Data augmentation and prior knowledge-based regularization for sound event localization and detection J Zhang, W Ding, L He DCASE 2019 Detection and Classification of Acoustic Scenes and Events 2019 …, 2019 | 31 | 2019 |
| Privacy leakage of adversarial training models in federated learning systems J Zhang, Y Chen, H Li Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 16 | 2022 |
| Improving out-of-distribution detection by learning from the deployment environment N Inkawhich, J Zhang, EK Davis, R Luley, Y Chen IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2022 | 15 | 2022 |
| Multi-Scale Time-Frequency Attention for Acoustic Event Detection J Zhang, W Ding, J Kang, L He Proc. Interspeech 2019, 3855-3859, 2019 | 14 | 2019 |
| Exploring Bit-Slice Sparsity in Deep Neural Networks for Efficient ReRAM-Based Deployment J Zhang, H Yang, F Chen, Y Wang, H Li The 5th Workshop on Energy Efficient Machine Learning and Cognitive …, 2019 | 11 | 2019 |
| Fine-grain inference on out-of-distribution data with hierarchical classification R Linderman, J Zhang, N Inkawhich, H Li, Y Chen Conference on Lifelong Learning Agents, 162-183, 2023 | 5 | 2023 |
| Can Targeted Adversarial Examples Transfer When the Source and Target Models Have No Label Space Overlap? N Inkawhich, KJ Liang, J Zhang, H Yang, H Li, Y Chen IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2021 | 5 | 2021 |
| Mintin: Maxout-based and input-normalized transformation invariant neural network J Zhang, K Jia, P Yang, F Qiao, Q Wei, X Liu, H Yang 2018 25th IEEE International Conference on Image Processing (ICIP), 3014-3018, 2018 | 4 | 2018 |
| Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models J Zhang, J Sun, E Yeats, Y Ouyang, M Kuo, J Zhang, H Yang, H Li arXiv preprint arXiv:2404.02936, 2024 | 2 | 2024 |
| Unsolvable Problem Detection: Evaluating Trustworthiness of Vision Language Models A Miyai, J Yang, J Zhang, Y Ming, Q Yu, G Irie, Y Li, H Li, Z Liu, K Aizawa arXiv preprint arXiv:2403.20331, 2024 | 2 | 2024 |
| SD-NAE: Generating Natural Adversarial Examples with Stable Diffusion Y Lin, J Zhang, Y Chen, H Li arXiv preprint arXiv:2311.12981, 2023 | 1 | 2023 |
| Sio: Synthetic in-distribution data benefits out-of-distribution detection J Zhang, N Inkawhich, R Linderman, R Luley, Y Chen, H Li arXiv preprint arXiv:2303.14531, 2023 | 1 | 2023 |
Hai LiClare Boothe Luce Professor of Electrical and Computer Engineering在 duke.edu 的电子邮件经过验证
