| A primer on contrastive pretraining in language processing: Methods, lessons learned, and perspectives N Rethmeier, I Augenstein ACM Computing Surveys 55 (10), 1-17, 2023 | 97 | 2023 |
| Neighborhood contrastive learning for scientific document representations with citation embeddings M Ostendorff, N Rethmeier, I Augenstein, B Gipp, G Rehm arXiv preprint arXiv:2202.06671, 2022 | 80 | 2022 |
| TX-Ray: Quantifying and Explaining Model-Knowledge Transfer in (Un-) Supervised NLP N Rethmeier, VK Saxena, I Augenstein UAI 2020, 2019 | 32 | 2019 |
| Long-tail zero and few-shot learning via contrastive pretraining on and for small data N Rethmeier, I Augenstein AAAI: Artificial Intelligence with Biased or Scarce Data Workshop, 2020 | 23* | 2020 |
| Detecting named entities and relations in German clinical reports R Roller, N Rethmeier, P Thomas, M Hübner, H Uszkoreit, O Staeck, ... Language Technologies for the Challenges of the Digital Age: 27th …, 2018 | 16 | 2018 |
| Learning comment controversy prediction in web discussions using incidentally supervised multi-task CNNs N Rethmeier, M Hübner, L Hennig EMNLP: Workshop on Computational Approaches to Subjectivity, Sentiment and …, 2018 | 14 | 2018 |
| EffiCare: better prognostic models via resource-efficient health embeddings N Rethmeier, NO Serbetci, S Möller, R Roller AMIA Annual Symposium Proceedings 2020, 1060, 2021 | 8 | 2021 |
| Neighborhood contrastive learning for scientific document representations with citation embeddings. arXiv M Ostendorff, N Rethmeier, I Augenstein arXiv preprint arXiv:2202.06671, 2022 | 6 | 2022 |
| VendorLink: An NLP approach for Identifying & Linking Vendor Migrants & Potential Aliases on Darknet Markets V Saxena, N Rethmeier, G Van Dijck, G Spanakis ACL: main track 61, 8619–8639, 2023 | 5 | 2023 |
| MoRTy: Unsupervised Learning of Task-specialized Word Embeddings by Autoencoding N Rethmeier, B Plank ACL: Workshop on Representation Learning for NLP 4, 2019 | 4 | 2019 |
| Common Round: Application of Language Technologies to Large-Scale Web Debates H Uszkoreit, A Gabryszak, L Hennig, J Steffen, R Ai, S Busemann, ... EACL 15, 5-8, 2017 | 3 | 2017 |
| Understanding and Analyzing Model Robustness and Knowledge-Transfer in Multilingual Neural Machine Translation using TX-Ray V Saxena, S Loáiciga, N Rethmeier arXiv preprint arXiv:2412.13881, 2024 | | 2024 |
| Efficient, Adaptable and Interpretable NLP N Rethmeier Copenhagen University, 2023 | | 2023 |
| Neighborhood contrastive learning for scientific document representations with citation embeddings M Ostendorff, N Rethmeier, I Augenstein, B Gipp, G Rehm EMNLP 2022, 2022 | | 2022 |
Isabelle AugensteinFull Professor, Department of Computer Science, University of Copenhagen確認したメール アドレス: di.ku.dk