| An image is worth 16x16 words: Transformers for image recognition at scale A Dosovitskiy, L Beyer, A Kolesnikov, D Weissenborn, X Zhai, ... arXiv preprint arXiv:2010.11929, 2020 | 25484 | 2020 |
| An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition G Tsatsaronis, G Balikas, P Malakasiotis, I Partalas, M Zschunke, ... BMC bioinformatics 16 (1), 1-28, 2015 | 690 | 2015 |
| Object-centric learning with slot attention F Locatello, D Weissenborn, T Unterthiner, A Mahendran, G Heigold, ... Advances in Neural Information Processing Systems 33, 11525-11538, 2020 | 518 | 2020 |
| Axial attention in multidimensional transformers J Ho, N Kalchbrenner, D Weissenborn, T Salimans arXiv preprint arXiv:1912.12180, 2019 | 399 | 2019 |
| Making Neural QA as Simple as Possible but not Simpler D Weissenborn, G Wiese, L Seiffe CoNLL, 2017 | 306* | 2017 |
| Scaling autoregressive video models D Weissenborn, O Täckström, J Uszkoreit arXiv preprint arXiv:1906.02634, 2019 | 183 | 2019 |
| Simple open-vocabulary object detection M Minderer, A Gritsenko, A Stone, M Neumann, D Weissenborn, ... European Conference on Computer Vision, 728-755, 2022 | 159 | 2022 |
| Colorization transformer M Kumar, D Weissenborn, N Kalchbrenner arXiv preprint arXiv:2102.04432, 2021 | 148 | 2021 |
| Neural Domain Adaptation for Biomedical Question Answering G Wiese, D Weissenborn, M Neves CoNLL, 2017 | 137* | 2017 |
| Dynamic Integration of Background Knowledge in Neural NLU Systems D Weissenborn, T Kočiský, C Dyer arXiv preprint arXiv:1706.02596, 2017 | 74* | 2017 |
| Differentiable patch selection for image recognition JB Cordonnier, A Mahendran, A Dosovitskiy, D Weissenborn, J Uszkoreit, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 69 | 2021 |
| Transformers for image recognition at scale A Dosovitskiy, L Beyer, A Kolesnikov, D Weissenborn, X Zhai, ... arXiv preprint arXiv:2010.11929, 2020 | 55 | 2020 |
| Multi-objective optimization for the joint disambiguation of nouns and named entities D Weissenborn, L Hennig, F Xu, H Uszkoreit Proceedings of the 53rd Annual Meeting of the Association for Computational …, 2015 | 47 | 2015 |
| Event linking with sentential features from convolutional neural networks S Krause, F Xu, H Uszkoreit, D Weissenborn Proceedings of the 20th SIGNLL Conference on Computational Natural Language …, 2016 | 40 | 2016 |
| Answering factoid questions in the biomedical domain. D Weissenborn, G Tsatsaronis, M Schroeder BioASQ@ CLEF 1094, 2013 | 31 | 2013 |
| Sar-graphs: A language resource connecting linguistic knowledge with semantic relations from knowledge graphs S Krause, L Hennig, A Moro, D Weissenborn, F Xu, H Uszkoreit, R Navigli Journal of Web Semantics 37, 112-131, 2016 | 28 | 2016 |
| Discovering relations between indirectly connected biomedical concepts D Weissenborn, M Schroeder, G Tsatsaronis Journal of biomedical semantics 6, 1-19, 2015 | 24 | 2015 |
| Cross-lingual candidate search for biomedical concept normalization R Roller, M Kittner, D Weissenborn, U Leser arXiv preprint arXiv:1805.01646, 2018 | 21 | 2018 |
| Separating answers from queries for neural reading comprehension D Weissenborn arXiv preprint arXiv:1607.03316, 2016 | 19 | 2016 |
| Jack the reader-A machine reading framework D Weissenborn, P Minervini, T Dettmers, I Augenstein, J Welbl, ... arXiv preprint arXiv:1806.08727, 2018 | 10 | 2018 |
