| Multimodal routing: Improving local and global interpretability of multimodal language analysis YHH Tsai, MQ Ma, M Yang, R Salakhutdinov, LP Morency Proceedings of the Conference on Empirical Methods in Natural Language …, 2020 | 101 | 2020 |
| M2lens: Visualizing and explaining multimodal models for sentiment analysis X Wang, J He, Z Jin, M Yang, Y Wang, H Qu IEEE Transactions on Visualization and Computer Graphics 28 (1), 802-812, 2021 | 84 | 2021 |
| Self-supervised representation learning with relative predictive coding YHH Tsai, MQ Ma, M Yang, H Zhao, LP Morency, R Salakhutdinov ICLR 2021, 2021 | 39 | 2021 |
| Improving lesion segmentation for diabetic retinopathy using adversarial learning Q Xiao, J Zou, M Yang, A Gaudio, K Kitani, A Smailagic, P Costa, M Xu International Conference on Image Analysis and Recognition, 333-344, 2019 | 39 | 2019 |
| Complex transformer: A framework for modeling complex-valued sequence M Yang, MQ Ma, D Li, YHH Tsai, R Salakhutdinov ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 38 | 2020 |
| Online Continual Learning of End-to-End Speech Recognition Models M Yang, I Lane, S Watanabe Interspeech 2022, 2022 | 30 | 2022 |
| Signal transformer: Complex-valued attention and meta-learning for signal recognition Y Peng, Y Dong, M Yang, S Lu, Q Shi ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 12 | 2024 |
| Towards noise-tolerant speech-referring video object segmentation: Bridging speech and text X Li, J Wang, X Xu, M Yang, F Yang, Y Zhao, R Singh, B Raj Proceedings of the 2023 Conference on Empirical Methods in Natural Language …, 2023 | 12 | 2023 |
| Paaploss: A Phonetic-Aligned Acoustic Parameter Loss for Speech Enhancement M Yang, J Konan, D Bick, Y Zeng, S Han, A Kumar, S Watanabe, B Raj ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 10 | 2023 |
| Improving Speech Enhancement through Fine-Grained Speech Characteristics M Yang, J Konan, D Bick, A Kumar, S Watanabe, B Raj Interspeech 2022, 2022 | 10 | 2022 |
| Backdoor attacks with input-unique triggers in nlp X Zhou, J Li, T Zhang, L Lyu, M Yang, J He Joint European Conference on Machine Learning and Knowledge Discovery in …, 2024 | 8 | 2024 |
| Simulating realistic speech overlaps improves multi-talker ASR M Yang, N Kanda, X Wang, J Wu, S Sivasankaran, Z Chen, J Li, ... ICASSP 2023, 2022 | 8 | 2022 |
| Sequence-level knowledge distillation for class-incremental end-to-end spoken language understanding U Cappellazzo, M Yang, D Falavigna, A Brutti arXiv preprint arXiv:2305.13899, 2023 | 6 | 2023 |
| Storing and querying large-scale spatio-temporal graphs with high-throughput edge insertions M Ding, M Yang, S Chen arXiv preprint arXiv:1904.09610, 2019 | 5 | 2019 |
| Usee: Unified speech enhancement and editing with conditional diffusion models M Yang, C Zhang, Y Xu, Z Xu, H Wang, B Raj, D Yu ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 4 | 2024 |
| Rethinking Voice-Face Correlation: A Geometry View X Li, Y Wen, M Yang, J Wang, R Singh, B Raj Proceedings of the 31st ACM International Conference on Multimedia, 2458-2467, 2023 | 4 | 2023 |
| Improving Continual Learning of Acoustic Scene Classification via Mutual Information Optimization M Yang, U Cappellazzo, X Li, B Raj ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 3 | 2024 |
| Evaluating and Improving Continual Learning in Spoken Language Understanding M Yang, X Li, U Cappellazzo, S Watanabe, B Raj arXiv preprint arXiv:2402.10427, 2024 | 2 | 2024 |
| Unifying robustness and fidelity: A comprehensive study of pretrained generative methods for speech enhancement in adverse conditions H Wang, M Yu, H Zhang, C Zhang, Z Xu, M Yang, Y Zhang, D Yu arXiv preprint arXiv:2309.09028, 2023 | 2 | 2023 |
| Taploss: A temporal acoustic parameter loss for speech enhancement BR Y Zeng, J Konan, S Han, D Bick, M Yang, A Kumar, S Watanabe ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 2* | 2023 |
Ruslan SalakhutdinovUPMC Professor, Machine Learning Department, CMU在 cs.cmu.edu 的电子邮件经过验证
