详见个人Google scholar:https://scholar.google.com/citations?user=KVeRu2QAAAAJ&hl=zh-CN
部分论文信息如下:
[1] Wu, Y., & Guo, Y. (2020, April). Dual adversarial co-learning for multi-domain text classification. In Proceedings of the AAAI conference on artificial intelligence (Vol. 34, No. 04, pp. 6438-6445). (AAAI, CCF-A, 清华A类)
[2] Wu, Y., Inkpen, D., & El-Roby, A. (2020). Dual mixup regularized learning for adversarial domain adaptation. In Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIX 16 (pp. 540-555). Springer International Publishing.(ECCV, CCF-B, 清华A类)
[3] Wu, Y., Inkpen, D., & El-Roby, A. (2021, June). Mixup regularized adversarial networks for multi-domain text classification. In ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 7733-7737). IEEE. (ICASSP, CCF-B, 清华B类)
[4] Wu, Y., Inkpen, D., & El-Roby, A. (2021). Towards category and domain alignment: Category-invariant feature enhancement for adversarial domain adaptation. In Proceedings of the IEEE/CVF International Conference on Computer Vision workshops (pp. 132-141). (ICCV workshop)
[5] Wu, Y., Inkpen, D., & El-Roby, A. (2021, April). Conditional Adversarial Networks for Multi-Domain Text Classification. In Proceedings of the Second Workshop on Domain Adaptation for NLP (pp. 16-27). (EACL workshop)
[6] Wu, Y., Inkpen, D., & El-Roby, A. (2022, May). Co-regularized adversarial learning for multi-domain text classification. In International Conference on Artificial Intelligence and Statistics (pp. 6690-6701). PMLR. (AISTATS, CCF-C, 清华B类)
[7] Wu, Y., Inkpen, D., & El-Roby, A. (2022, May). Maximum Batch Frobenius Norm for Multi-Domain Text Classification. In ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 3763-3767). IEEE. (ICASSP, CCF-B, 清华B类)
[8] Chang, Y., Wang, X., Wang, J., Wu, Y., Zhu, K., Chen, H., ...& Xie, X. (2023). A survey on evaluation of large language models. arXiv preprint arXiv:2307.03109.