| Colight: Learning network-level cooperation for traffic signal control H Wei, N Xu, H Zhang, G Zheng, X Zang, C Chen, W Zhang, Y Zhu, K Xu, ... Proceedings of the 28th ACM international conference on information and …, 2019 | 367 | 2019 |
| Toward a thousand lights: Decentralized deep reinforcement learning for large-scale traffic signal control C Chen, H Wei, N Xu, G Zheng, M Yang, Y Xiong, K Xu, Z Li Proceedings of the AAAI conference on artificial intelligence 34 (04), 3414-3421, 2020 | 345 | 2020 |
| Autodan: Generating stealthy jailbreak prompts on aligned large language models X Liu, N Xu, M Chen, C Xiao ICLR 2024, 2023 | 185 | 2023 |
| Metalight: Value-based meta-reinforcement learning for traffic signal control X Zang, H Yao, G Zheng, N Xu, K Xu, Z Li Proceedings of the AAAI conference on artificial intelligence 34 (01), 1153-1160, 2020 | 179 | 2020 |
| Interpretability and fairness evaluation of deep learning models on MIMIC-IV dataset C Meng, L Trinh, N Xu, J Enouen, Y Liu Scientific Reports 12 (1), 7166, 2022 | 125 | 2022 |
| Diagnosing reinforcement learning for traffic signal control G Zheng, X Zang, N Xu, H Wei, Z Yu, V Gayah, K Xu, Z Li arXiv preprint arXiv:1905.04716, 2019 | 123 | 2019 |
| Evaluating Large Language Models on Controlled Generation Tasks J Sun, Y Tian, W Zhou, N Xu, Q Hu, R Gupta, JF Wieting, N Peng, X Ma EMNLP 2023, 2023 | 30 | 2023 |
| A multi-scale time-series dataset with benchmark for machine learning in decarbonized energy grids X Zheng, N Xu, L Trinh, D Wu, T Huang, S Sivaranjani, Y Liu, L Xie Scientific Data 9 (1), 359, 2022 | 30 | 2022 |
| Mimic-if: Interpretability and fairness evaluation of deep learning models on mimic-iv dataset C Meng, L Trinh, N Xu, Y Liu arXiv preprint arXiv:2102.06761, 2021 | 22 | 2021 |
| Cognitive overload: Jailbreaking large language models with overloaded logical thinking N Xu, F Wang, B Zhou, BZ Li, C Xiao, M Chen NAACL 2024 (Findings), 2023 | 19 | 2023 |
| Targeted knowledge transfer for learning traffic signal plans N Xu, G Zheng, K Xu, Y Zhu, Z Li Advances in Knowledge Discovery and Data Mining: 23rd Pacific-Asia …, 2019 | 17 | 2019 |
| Density-aware differentially private textual perturbations using truncated Gumbel noise N Xu, O Feyisetan, A Aggarwal, Z Xu, N Teissier The International FLAIRS Conference Proceedings 34, 2021 | 15 | 2021 |
| Does your model classify entities reasonably? diagnosing and mitigating spurious correlations in entity typing N Xu, F Wang, B Li, M Dong, M Chen EMNLP 2022, 2022 | 14 | 2022 |
| MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding F Wang, X Fu, JY Huang, Z Li, Q Liu, X Liu, MD Ma, N Xu, W Zhou, ... arXiv preprint arXiv:2406.09411, 2024 | 10 | 2024 |
| Differentially private adversarial robustness through randomized perturbations N Xu, O Feyisetan, A Aggarwal, Z Xu, N Teissier arXiv preprint arXiv:2009.12718, 2020 | 5 | 2020 |
| Toward a thousand lights: Decentralized deep reinforcement learning for large-scale traffic signal control HW Chacha Chen, N Xu, G Zheng, M Yang, Y Xiong, K Xu, Z Li Proceedings of the thirty-fourth AAAI conference on artificial intelligence …, 2020 | 5 | 2020 |
| Attention-based hierarchical recurrent neural network for phenotype classification N Xu, Y Shen, Y Zhu Advances in Knowledge Discovery and Data Mining: 23rd Pacific-Asia …, 2019 | 5 | 2019 |
| Look-back Decoding for Open-Ended Text Generation N Xu, C Zhou, A Celikyilmaz, X Ma EMNLP 2023, 2023 | 4 | 2023 |
| Dense Retrieval as Indirect Supervision for Large-space Decision Making N Xu, F Wang, M Dong, M Chen EMNLP 2023 (Findings), 2023 | 3 | 2023 |
| CEO: Corpus-based Open-Domain Event Ontology Induction N Xu, H Zhang, J Chen EACL 2024 (Findings), 2023 | 2 | 2023 |
