| Beit: Bert pre-training of image transformers H Bao, L Dong, S Piao, F Wei arXiv preprint arXiv:2106.08254, 2021 | 3238 | 2021 |
| Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks X Li, X Yin, C Li, P Zhang, X Hu, L Zhang, L Wang, H Hu, L Dong, F Wei, ... Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 2276 | 2020 |
| Swin transformer v2: Scaling up capacity and resolution Z Liu, H Hu, Y Lin, Z Yao, Z Xie, Y Wei, J Ning, Y Cao, Z Zhang, L Dong, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 2269 | 2022 |
| Vl-bert: Pre-training of generic visual-linguistic representations W Su, X Zhu, Y Cao, B Li, L Lu, F Wei, J Dai arXiv preprint arXiv:1908.08530, 2019 | 1973 | 2019 |
| Wavlm: Large-scale self-supervised pre-training for full stack speech processing S Chen, C Wang, Z Chen, Y Wu, S Liu, Z Chen, J Li, N Kanda, T Yoshioka, ... IEEE Journal of Selected Topics in Signal Processing 16 (6), 1505-1518, 2022 | 1969 | 2022 |
| Unified language model pre-training for natural language understanding and generation L Dong, N Yang, W Wang, F Wei, X Liu, Y Wang, J Gao, M Zhou, HW Hon 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), 2019 | 1906 | 2019 |
| Learning sentiment-specific word embedding for twitter sentiment classification D Tang, F Wei, N Yang, M Zhou, T Liu, B Qin Proceedings of the 52nd Annual Meeting of the Association for Computational …, 2014 | 1645 | 2014 |
| Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers W Wang, F Wei, L Dong, H Bao, N Yang, M Zhou Advances in neural information processing systems 33, 5776-5788, 2020 | 1338 | 2020 |
| Adaptive Recursive Neural Network for Target-dependent Twitter Sentiment Classification L Dong, F Wei, C Tan, D TangΤ, M Zhou, K Xu ACL, 2014 | 1277 | 2014 |
| Layoutlm: Pre-training of text and layout for document image understanding Y Xu, M Li, L Cui, S Huang, F Wei, M Zhou Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 883 | 2020 |
| HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization X Zhang, F Wei, M Zhou ACL, 2019 | 866* | 2019 |
| Gated self-matching networks for reading comprehension and question answering W Wang, N Yang, F Wei, B Chang, M Zhou Proceedings of the 55th Annual Meeting of the Association for Computational …, 2017 | 852 | 2017 |
| Kosmos-2: Grounding multimodal large language models to the world Z Peng, W Wang, L Dong, Y Hao, S Huang, S Ma, F Wei arXiv preprint arXiv:2306.14824, 2023 | 705 | 2023 |
| Neural codec language models are zero-shot text to speech synthesizers C Wang, S Chen, Y Wu, Z Zhang, L Zhou, S Liu, Z Chen, Y Liu, H Wang, ... arXiv preprint arXiv:2301.02111, 2023 | 682 | 2023 |
| Topic sentiment analysis in twitter: a graph-based hashtag sentiment classification approach X Wang, F Wei, X Liu, M Zhou, M Zhang Proceedings of the 20th ACM international conference on Information and …, 2011 | 643 | 2011 |
| Recognizing named entities in tweets X Liu, S Zhang, F Wei, M Zhou Proceedings of the 49th annual meeting of the association for computational …, 2011 | 620 | 2011 |
| Image as a foreign language: Beit pretraining for vision and vision-language tasks W Wang, H Bao, L Dong, J Bjorck, Z Peng, Q Liu, K Aggarwal, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 614 | 2023 |
| Question answering over freebase with multi-column convolutional neural networks L Dong, F Wei, M Zhou, K Xu Proceedings of the 53rd Annual Meeting of the Association for Computational …, 2015 | 607 | 2015 |
| Layoutlmv2: Multi-modal pre-training for visually-rich document understanding Y Xu, Y Xu, T Lv, L Cui, F Wei, G Wang, Y Lu, D Florencio, C Zhang, ... arXiv preprint arXiv:2012.14740, 2020 | 579 | 2020 |
| Knowledge neurons in pretrained transformers D Dai, L Dong, Y Hao, Z Sui, B Chang, F Wei arXiv preprint arXiv:2104.08696, 2021 | 576 | 2021 |
Li DongMicrosoft ResearchE-mailová adresa ověřena na: microsoft.com
