| Learning concise and descriptive attributes for visual recognition A Yan, Y Wang, Y Zhong, C Dong, Z He, Y Lu, WY Wang, J Shang, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 38 | 2023 |
| Towards adaptive residual network training: A neural-ode perspective C Dong, L Liu, Z Li, J Shang International conference on machine learning, 2616-2626, 2020 | 34 | 2020 |
| Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting C Dong, L Liu, J Shang Advances in Neural Information Processing Systems (Oral) 35, 17556-17567, 2022 | 23* | 2022 |
| Robust and interpretable medical image classifiers via concept bottleneck models A Yan, Y Wang, Y Zhong, Z He, P Karypis, Z Wang, C Dong, A Gentili, ... arXiv preprint arXiv:2310.03182, 2023 | 18 | 2023 |
| Bfclass: A backdoor-free text classification framework Z Li, D Mekala, C Dong, J Shang arXiv preprint arXiv:2109.10855, 2021 | 18 | 2021 |
| Data quality matters for adversarial training: An empirical study C Dong, L Liu, J Shang arXiv preprint arXiv:2102.07437, 2021 | 15* | 2021 |
| LOPS: Learning order inspired pseudo-label selection for weakly supervised text classification D Mekala, C Dong, J Shang arXiv preprint arXiv:2205.12528, 2022 | 11 | 2022 |
| Bridging discrete and backpropagation: Straight-through and beyond L Liu, C Dong, X Liu, B Yu, J Gao Advances in Neural Information Processing Systems 36, 2024 | 8 | 2024 |
| Toward student-oriented teacher network training for knowledge distillation C Dong, L Liu, J Shang The Twelfth International Conference on Learning Representations, 2024 | 5* | 2024 |
| Perturbation Deterioration: The Other Side of Catastrophic Overfitting Z Li, L Liu, C Dong, J Shang | 4* | |
| Debiasing made state-of-the-art: Revisiting the simple seed-based weak supervision for text classification C Dong, Z Wang, J Shang arXiv preprint arXiv:2305.14794, 2023 | 3 | 2023 |
| " Average" Approximates" First Principal Component"? An Empirical Analysis on Representations from Neural Language Models Z Wang, C Dong, J Shang arXiv preprint arXiv:2104.08673, 2021 | 3 | 2021 |
| Physics-Informed Data Denoising for Real-Life Sensing Systems X Zhang, X Fu, D Teng, C Dong, K Vijayakumar, J Zhang, RR Chowdhury, ... Proceedings of the 21st ACM Conference on Embedded Networked Sensor Systems …, 2023 | 1 | 2023 |
| Understand and modularize generator optimization in ELECTRA-style pretraining C Dong, L Liu, H Cheng, J Shang, J Gao, X Liu International Conference on Machine Learning, 8244-8259, 2023 | 1 | 2023 |
| SELFOOD: Self-Supervised Out-Of-Distribution Detection via Learning to Rank D Mekala, A Samavedhi, C Dong, J Shang arXiv preprint arXiv:2305.14696, 2023 | 1 | 2023 |
| When is the consistent prediction likely to be a correct prediction? A Nguyen, D Mekala, C Dong, J Shang arXiv preprint arXiv:2407.05778, 2024 | | 2024 |
| Text Grafting: Near-Distribution Weak Supervision for Minority Classes in Text Classification L Peng, Y Gu, C Dong, Z Wang, J Shang arXiv preprint arXiv:2406.11115, 2024 | | 2024 |
| Evaluating the Smooth Control of Attribute Intensity in Text Generation with LLMs S Zhou, F Yao, C Dong, Z Wang, J Shang arXiv preprint arXiv:2406.04460, 2024 | | 2024 |
| Fast-ELECTRA for Efficient Pre-training C Dong, L Liu, H Cheng, J Shang, J Gao, X Liu arXiv preprint arXiv:2310.07347, 2023 | | 2023 |
| Generalized Uncertainty of Deep Neural Networks: Taxonomy and Applications C Dong arXiv preprint arXiv:2302.01440, 2023 | | 2023 |
Jingbo ShangAssistant Professor, UC San DiegoVerified email at ucsd.edu
