| 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 Advances in neural information processing systems 32, 2019 | 1880 | 2019 |
| 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 | 1285 | 2020 |
| 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 | 617 | 2023 |
| 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 | 570 | 2023 |
| Vlmo: Unified vision-language pre-training with mixture-of-modality-experts H Bao, W Wang, L Dong, Q Liu, OK Mohammed, K Aggarwal, S Som, ... Advances in Neural Information Processing Systems 35, 32897-32912, 2022 | 547 | 2022 |
| Language is not all you need: Aligning perception with language models S Huang, L Dong, W Wang, Y Hao, S Singhal, S Ma, T Lv, L Cui, ... Advances in Neural Information Processing Systems 36, 72096-72109, 2023 | 483 | 2023 |
| Unilmv2: Pseudo-masked language models for unified language model pre-training H Bao, L Dong, F Wei, W Wang, N Yang, X Liu, Y Wang, J Gao, S Piao, ... International conference on machine learning, 642-652, 2020 | 444 | 2020 |
| InfoXLM: An information-theoretic framework for cross-lingual language model pre-training Z Chi, L Dong, F Wei, N Yang, S Singhal, W Wang, X Song, XL Mao, ... arXiv preprint arXiv:2007.07834, 2020 | 362 | 2020 |
| Minilmv2: Multi-head self-attention relation distillation for compressing pretrained transformers W Wang, H Bao, S Huang, L Dong, F Wei arXiv preprint arXiv:2012.15828, 2020 | 234 | 2020 |
| Graph-based dependency parsing with bidirectional LSTM W Wang, B Chang Proceedings of the 54th Annual Meeting of the Association for Computational …, 2016 | 188 | 2016 |
| The era of 1-bit llms: All large language models are in 1.58 bits S Ma, H Wang, L Ma, L Wang, W Wang, S Huang, L Dong, R Wang, J Xue, ... arXiv preprint arXiv:2402.17764 1, 2024 | 175 | 2024 |
| Longnet: Scaling transformers to 1,000,000,000 tokens J Ding, S Ma, L Dong, X Zhang, S Huang, W Wang, N Zheng, F Wei arXiv preprint arXiv:2307.02486, 2023 | 164 | 2023 |
| Multiway attention networks for modeling sentence pairs. C Tan, F Wei, W Wang, W Lv, M Zhou IJCAI, 4411-4417, 2018 | 157 | 2018 |
| Cross-lingual natural language generation via pre-training Z Chi, L Dong, F Wei, W Wang, XL Mao, H Huang Proceedings of the AAAI conference on artificial intelligence 34 (05), 7570-7577, 2020 | 149 | 2020 |
| Language models are general-purpose interfaces Y Hao, H Song, L Dong, S Huang, Z Chi, W Wang, S Ma, F Wei arXiv preprint arXiv:2206.06336, 2022 | 105 | 2022 |
| Learning to ask unanswerable questions for machine reading comprehension H Zhu, L Dong, F Wei, W Wang, B Qin, T Liu arXiv preprint arXiv:1906.06045, 2019 | 54 | 2019 |
| Kosmos-2.5: A multimodal literate model T Lv, Y Huang, J Chen, Y Zhao, Y Jia, L Cui, S Ma, Y Chang, S Huang, ... arXiv preprint arXiv:2309.11419, 2023 | 53 | 2023 |
| Harvesting and refining question-answer pairs for unsupervised QA Z Li, W Wang, L Dong, F Wei, K Xu arXiv preprint arXiv:2005.02925, 2020 | 52 | 2020 |
| Grounding multimodal large language models to the world Z Peng, W Wang, L Dong, Y Hao, S Huang, S Ma, Q Ye, F Wei The Twelfth International Conference on Learning Representations, 2024 | 50 | 2024 |
Furu WeiPartner Research Manager, Microsoft ResearchOverená e-mailová adresa na: microsoft.com
