| Adversarial attacks and defenses in images, graphs and text: A review H Xu, Y Ma, H Liu, D Deb, H Liu, J Tang, AK Jain International Journal of Automation and Computing 17 (2), 151-178, 2020 | 821 | 2020 |
| Trustworthy AI: A Computational Perspective H Liu, Y Wang, W Fan, X Liu, Y Li, S Jain, Y Liu, AK Jain, J Tang ACM Transactions on Intelligent Systems and Technology, 2021 | 271 | 2021 |
| Self-supervised learning on graphs: Deep insights and new direction W Jin, T Derr, H Liu, Y Wang, S Wang, Z Liu, J Tang arXiv preprint arXiv:2006.10141, 2020 | 243 | 2020 |
| Does Gender Matter? Towards Fairness in Dialogue Systems H Liu, J Dacon, W Fan, H Liu, Z Liu, J Tang COLING 2020, 4403–4416, 2019 | 131 | 2019 |
| AutoEmb: Automated embedding dimensionality search in streaming recommendations X Zhao, H Liu, W Fan, H Liu, J Tang, C Wang, M Chen, X Zheng, X Liu, ... ICDM 2021, 896-905, 2021 | 121 | 2021 |
| Automated Embedding Size Search in Deep Recommender Systems H Liu, X Zhao, C Wang, X Liu, J Tang SIGIR 2020, 2307-2316, 2020 | 91 | 2020 |
| Mitigating Gender Bias for Neural Dialogue Generation with Adversarial Learning H Liu, W Wang, Y Wang, H Liu, Z Liu, J Tang EMNLP 2020, 893-903, 2020 | 71 | 2020 |
| AutoDim: Field-aware Embedding Dimension Searchin Recommender Systems X Zhao, H Liu, H Liu, J Tang, W Guo, J Shi, S Wang, H Gao, B Long Web Conference 2021, 3015-3022, 2021 | 65 | 2021 |
| AutoLoss: Automated Loss Function Search in Recommendations X Zhao, H Liu, W Fan, H Liu, J Tang, C Wang KDD 2021, 3959–3967, 2021 | 62 | 2021 |
| Fairly adaptive negative sampling for recommendations X Chen, W Fan, J Chen, H Liu, Z Liu, Z Zhang, Q Li Web Conference 2023, 3723–3733, 2023 | 37 | 2023 |
| MMMLP: Multi-modal Multilayer Perceptron for Sequential Recommendations J Liang, X Zhao, M Li, Z Zhang, W Wang, H Liu, Z Liu Web Conference 2023, 1109-1117, 2023 | 36 | 2023 |
| Memory-efficient embedding for recommendations X Zhao, H Liu, H Liu, J Tang, W Guo, J Shi, S Wang, H Gao, B Long arXiv preprint arXiv:2006.14827, 2020 | 35 | 2020 |
| Does Gender Matter in the News? Detecting and Examining Gender Bias in News Articles J Dacon, H Liu IC2S2 2021, 2021 | 34 | 2021 |
| The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification H Liu, W Jin, H Karimi, Z Liu, J Tang ACL Findings 2021, 74–85, 2021 | 33 | 2021 |
| Rating Distribution Calibration for Selection Bias Mitigation in Recommendations H Liu, D Tang, J Yang, X Zhao, H Liu, J Tang, Y Cheng Web Conference 2022, 2048-2057, 2022 | 25 | 2022 |
| Say What I Want: Towards the Dark Side of Neural Dialogue Models H Liu, T Derr, Z Liu, J Tang arXiv preprint arXiv:1909.06044, 2019 | 21 | 2019 |
| Neural Multi-Task Learning for Teacher Question Detection in Online Classrooms GY Huang, J Chen, H Liu, W Fu, W Ding, J Tang, S Yang, G Li, Z Liu AIED 2020, 269-281, 2020 | 19 | 2020 |
| Toward annotator group bias in crowdsourcing H Liu, J Thekinen, S Mollaoglu, D Tang, J Yang, Y Cheng, H Liu, J Tang ACL 2022, 1797–1806, 2021 | 17 | 2021 |
| Effective Representing of Information Network by Variational Autoencoder. H Li, H Wang, Z Yang, H Liu IJCAI 2017, 2103-2109, 2017 | 15 | 2017 |
| Chat as expected: Learning to manipulate black-box neural dialogue models H Liu, Z Wang, T Derr, J Tang arXiv preprint arXiv:2005.13170, 2020 | 13 | 2020 |
Jiliang TangUniversity Foundation Professor of Computer Science and Engineering, Michigan State UniversityVerified email at msu.edu