Anders Søgaard
Professor
Natural Language Processing
Universitetsparken 1
2100 København Ø
Department of Communication
Karen Blixens Plads 8
2300 København S
- Published
Higher-order Comparisons of Sentence Encoder Representations
vqc439, V., Kulmizev, A., Hill, F., Low, D. M. L. & Søgaard, Anders, 2019, Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing. Association for Computational Linguistics, p. 5838–5845Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Multilingual Negation Scope Resolution for Clinical Text
lwp876, L. & Søgaard, Anders, 2022, Proceedings of the 12th International Workshop on Health Text Mining and Information Analysis. Association for Computational Linguistics, p. 7–18Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Zero-Shot Dependency Parsing with Worst-Case Aware Automated Curriculum Learning
de Lhoneux, M., Zhang, S. & Søgaard, Anders, 2022, ACL 2022 - 60th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Short Papers). Muresan, S., Nakov, P. & Villavicencio, A. (eds.). Association for Computational Linguistics (ACL), p. 578-587Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Sociolectal Analysis of Pretrained Language Models
Zhang, S., Zhang, X., Zhang, W. & Søgaard, Anders, 2021, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, p. 4581–4588Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Learning finite state word representations for unsupervised Twitter adaptation of POS taggers
Wulff, J. & Søgaard, Anders, 2015, ACL 2015 Workshop on Noisy User-generated Text (W-NUT). Red Hook, NY: Association for Computational LinguisticsResearch output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Are All Good Word Vector Spaces Isomorphic?
Vulic, I., Ruder, S. & Søgaard, Anders, 2020, Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). Association for Computational Linguistics, p. 3178–3192Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Parsing as pretraining
Vilares, D., Strzyz, M., Søgaard, Anders & Gómez-Rodrıguez, C., 2020, Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2020). AAAI Press, p. 9114-9121.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Better, Faster, Stronger Sequence Tagging Constituent Parsers
Vilares, D., Abdou, M. & Søgaard, Anders, 2019, Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Association for Computational Linguistics, p. 3372-3383Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
A systematic comparison of methods for low-resource dependency parsing on genuinely low-resource languages
Vania, C., Kementchedjhieva, Yova Radoslavova, Søgaard, Anders & Lopez, A., 2019, Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, p. 1105-1116Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Spurious Correlations in Cross-Topic Argument Mining
Jakobsen, Terne Sasha Thorn, Barrett, M. & Søgaard, Anders, 2021, Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics. Association for Computational Linguistics, p. 263-277Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
ID: 13266
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Multilingual projection for parsing truly low resource languages
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Multi-task Learning of Pairwise Sequence Classification Tasks Over Disparate Label Spaces
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283
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Reading metrics for estimating task efficiency with MT output
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