| Chinese song iambics generation with neural attention-based model Q Wang, T Luo, D Wang, C Xing IJCAI 2016, 2016 | 113 | 2016 |
| Can machine generate traditional chinese poetry? a feigenbaum test Q Wang, T Luo, D Wang BICS 2016, 2016 | 39 | 2016 |
| The Rich Get Richer: Disparate Impact of Semi-Supervised Learning Z Zhu, T Luo, Y Liu ICLR 2022, 2022 | 38 | 2022 |
| To aggregate or not? learning with separate noisy labels J Wei, Z Zhu, T Luo, E Amid, A Kumar, Y Liu KDD 2023, 2023 | 33 | 2023 |
| Learning from LDA using deep neural networks D Zhang, T Luo, D Wang NLPCC 2016, 2016 | 30 | 2016 |
| Stochastic top-k listnet T Luo, D Wang, R Liu, Y Pan EMNLP 2015, 2015 | 19 | 2015 |
| Speech production under uncertainty: How do job applicants experience and communicate with an AI interviewer? B Liu, L Wei, M Wu, T Luo Journal of Computer-Mediated Communication, 2023 | 12 | 2023 |
| Machine truth serum T Luo, Y Liu AAAI 2023, 2023 | 5* | 2023 |
| Research Replication Prediction Using Weakly Supervised Learning T Luo, X Li, H Wang, Y Liu ENNLP 2020, 2020 | 5 | 2020 |
| Interpretable Research Replication Prediction via Variational Contextual Consistency Sentence Masking T Luo, R Meng, XE Wang, Y Liu ACL 2022, 2022 | 4 | 2022 |