Nils Rethmeier
PhD Student
Natural Language Processing
Universitetsparken 1, 2100 København Ø
1 - 5 out of 5Page size: 10
- Published
Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings
Ostendorff, M., Rethmeier, Nils, Augenstein, Isabelle, Gipp, B. & Rehm, G., 2022, Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (ACL), p. 11670–11688Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Long-Tail Zero and Few-Shot Learning via Contrastive Pretraining on and for Small Data
Rethmeier, Nils & Augenstein, Isabelle, 2022, In: Computer Sciences & Mathematics Forum . 3, 18 p., 10.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Efficient, Adaptable and Interpretable NLP
Rethmeier, Nils, 2023, Department of Computer Science, Faculty of Science, University of Copenhagen. 195 p.Research output: Book/Report › Ph.D. thesis › Research
- Published
A Primer on Contrastive Pretraining in Language Processing: Methods, Lessons Learned, and Perspectives
Rethmeier, Nils & Augenstein, Isabelle, 2023, In: ACM Computing Surveys. 55, 10, 17 p., 203.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
TX-Ray: Quantifying and Explaining Model-Knowledge Transfer in (Un-)Supervised NLP
Rethmeier, Nils, Saxena, V. K. & Augenstein, Isabelle, 2020, Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAII). Peters, J. & Sontag, D. (eds.). PMLR, p. 440-449 (Proceedings of Machine Learning Research, Vol. 124).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
ID: 238718757
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TX-Ray: Quantifying and Explaining Model-Knowledge Transfer in (Un-)Supervised NLP
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Published