| Multi-task label embedding for text classification H Zhang, L Xiao, W Chen, Y Wang, Y Jin arXiv preprint arXiv:1710.07210, 2017 | 111 | 2017 |
| EEG characteristics of children with attention-deficit/hyperactivity disorder H Chen, W Chen, Y Song, L Sun, X Li Neuroscience 406, 444-456, 2019 | 82 | 2019 |
| Mcapsnet: Capsule network for text with multi-task learning L Xiao, H Zhang, W Chen, Y Wang, Y Jin Proceedings of the 2018 conference on empirical methods in natural language …, 2018 | 55 | 2018 |
| Diagnosing the first-order logical reasoning ability through logicnli J Tian, Y Li, W Chen, L Xiao, H He, Y Jin Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 43 | 2021 |
| Gated multi-task network for text classification L Xiao, H Zhang, W Chen Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 40 | 2018 |
| Disentangled makeup transfer with generative adversarial network H Zhang, W Chen, H He, Y Jin arXiv preprint arXiv:1907.01144, 2019 | 35 | 2019 |
| Towards an understanding of large language models in software engineering tasks Z Zheng, K Ning, J Chen, Y Wang, W Chen, L Guo, W Wang arXiv preprint arXiv:2308.11396, 2023 | 27 | 2023 |
| De-confounded variational encoder-decoder for logical table-to-text generation W Chen, J Tian, Y Li, H He, Y Jin Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 24 | 2021 |
| Learning what to share: Leaky multi-task network for text classification L Xiao, H Zhang, W Chen, Y Wang, Y Jin Proceedings of the 27th International Conference on Computational …, 2018 | 24 | 2018 |
| Transformable Convolutional Neural Network for Text Classification. L Xiao, H Zhang, W Chen, Y Wang, Y Jin IJCAI, 4496-4502, 2018 | 18 | 2018 |
| A semantically consistent and syntactically variational encoder-decoder framework for paraphrase generation W Chen, J Tian, L Xiao, H He, Y Jin Proceedings of the 28th international conference on computational …, 2020 | 17 | 2020 |
| Exploring logically dependent multi-task learning with causal inference W Chen, J Tian, L Xiao, H He, Y Jin Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 16 | 2020 |
| Weakly supervised neural symbolic learning for cognitive tasks J Tian, Y Li, W Chen, L Xiao, H He, Y Jin Proceedings of the AAAI Conference on Artificial Intelligence 36 (5), 5888-5896, 2022 | 11 | 2022 |
| Llm-guided multi-view hypergraph learning for human-centric explainable recommendation Z Chu, Y Wang, Q Cui, L Li, W Chen, S Li, Z Qin, K Ren arXiv preprint arXiv:2401.08217, 2024 | 8 | 2024 |
| Dependent multi-task learning with causal intervention for image captioning W Chen, J Tian, C Fan, H He, Y Jin arXiv preprint arXiv:2105.08573, 2021 | 7 | 2021 |
| Show, attend and translate: Unpaired multi-domain image-to-image translation with visual attention H Zhang, W Chen, J Tian, Y Wang, Y Jin arXiv preprint arXiv:1811.07483, 2018 | 5 | 2018 |
| To What Extent Do Natural Language Understanding Datasets Correlate to Logical Reasoning? A Method for Diagnosing Logical Reasoning. Y Li, J Tian, W Chen, C Fan, H He, Y Jin Proceedings of the 29th International Conference on Computational …, 2022 | 4 | 2022 |
| Chain-of-thought tuning: Masked language models can also think step by step in natural language understanding C Fan, J Tian, Y Li, W Chen, H He, Y Jin arXiv preprint arXiv:2310.11721, 2023 | 3 | 2023 |
| Accurate use of label dependency in multi-label text classification through the lens of causality C Fan, W Chen, J Tian, Y Li, H He, Y Jin Applied Intelligence 53 (19), 21841-21857, 2023 | 3 | 2023 |
| Improving the out-of-distribution generalization capability of language models: Counterfactually-augmented data is not enough C Fan, W Chen, J Tian, Y Li, H He, Y Jin ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 3 | 2023 |
