| Uncertainty Aware Semi-Supervised Learning on Graph Data X Zhao, F Chen, S Hu, JH Cho Advances in Neural Information Processing Systems (NeurIPS), 2020, 2020 | 114 | 2020 |
| RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning K Killamsetty, X Zhao, F Chen, R Iyer Advances in Neural Information Processing Systems (NeurIPS), 2021, 2021 | 79 | 2021 |
| Domain specialization as the key to make large language models disruptive: A comprehensive survey C Ling, X Zhao, J Lu, C Deng, C Zheng, J Wang, T Chowdhury, Y Li, ... arXiv preprint arXiv:2305.18703, 2023 | 67 | 2023 |
| Beyond one-model-fits-all: A survey of domain specialization for large language models C Ling, X Zhao, J Lu, C Deng, C Zheng, J Wang, T Chowdhury, Y Li, ... arXiv preprint arXiv:2305.18703 1, 2023 | 37 | 2023 |
| Multifaceted Uncertainty Estimation for Label-Efficient Deep Learning W Shi, X Zhao, F Chen, Q Yu Advances in Neural Information Processing Systems (NeurIPS), 2020, 2020 | 32 | 2020 |
| Quantifying Classification Uncertainty using Regularized Evidential Neural Networks X Zhao, Y Ou, L Kaplan, F Chen, JH Cho AAAI 2019 Fall Symposium Series, Artificial Intelligence in Government and …, 2019 | 23 | 2019 |
| Multidimensional Uncertainty-Aware Evidential Neural Networks Y Hu, Y Ou, X Zhao, JH Cho, F Chen AAAI Conference on Artificial Intelligence (AAAI), 2021, 2020 | 21 | 2020 |
| CLEAR: Contrastive-Prototype Learning with Drift Estimation for Resource Constrained Stream Mining Z Wang, Y Chen, C Zhao, Y Lin, X Zhao, H Tao, Y Wang, L Khan The Web Conference 2021 (WWW), 1351-1362, 2021 | 20 | 2021 |
| Large language models can be good privacy protection learners Y Xiao, Y Jin, Y Bai, Y Wu, X Yang, X Luo, W Yu, X Zhao, Y Liu, H Chen, ... arXiv preprint arXiv:2310.02469, 2023 | 19 | 2023 |
| Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty Estimation L Xu, X Zhang, X Zhao, H Chen, F Chen, JD Choi Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 17 | 2021 |
| Robust semi-supervised learning with out of distribution data X Zhao, K Krishnateja, R Iyer, F Chen arXiv preprint arXiv:2010.03658 2 (3), 2020 | 17 | 2020 |
| Uncertainty-based decision making using deep reinforcement learning X Zhao, S Hu, JH Cho, F Chen 2019 22th International Conference on Information Fusion (FUSION), 1-8, 2019 | 17 | 2019 |
| Deep learning for predicting dynamic uncertain opinions in network data X Zhao, F Chen, JH Cho 2018 IEEE International Conference on Big Data (Big Data), 1150-1155, 2018 | 16 | 2018 |
| A survey on uncertainty reasoning and quantification for decision making: Belief theory meets deep learning Z Guo, Z Wan, Q Zhang, X Zhao, F Chen, JH Cho, Q Zhang, LM Kaplan, ... arXiv preprint arXiv:2206.05675, 2022 | 14 | 2022 |
| Seed: Sound event early detection via evidential uncertainty X Zhao, X Zhang, W Cheng, W Yu, Y Chen, H Chen, F Chen ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 11 | 2022 |
| Improving open information extraction with large language models: A study on demonstration uncertainty C Ling, X Zhao, X Zhang, Y Liu, W Cheng, H Wang, Z Chen, T Osaki, ... arXiv preprint arXiv:2309.03433, 2023 | 9 | 2023 |
| Calibrate automated graph neural network via hyperparameter uncertainty X Yang, J Wang, X Zhao, S Li, Z Tao Proceedings of the 31st ACM International Conference on Information …, 2022 | 9 | 2022 |
| Knowledge-enhanced neural machine reasoning: A review T Chowdhury, C Ling, X Zhang, X Zhao, G Bai, J Pei, H Chen, L Zhao arXiv preprint arXiv:2302.02093, 2023 | 8 | 2023 |
| Deep learning based scalable inference of uncertain opinions X Zhao, F Chen, JH Cho 2018 IEEE International Conference on Data Mining (ICDM), 807-816, 2018 | 8 | 2018 |
| Dynamic prompting: A unified framework for prompt tuning X Yang, W Cheng, X Zhao, W Yu, L Petzold, H Chen arXiv preprint arXiv:2303.02909, 2023 | 7 | 2023 |
Feng ChenDepartment of Computer Science, UT DallasVerified email at utdallas.edu
