Anders Søgaard
Professor
Natural Language Processing
Universitetsparken 1
2100 København Ø
Department of Communication
Karen Blixens Plads 8
2300 København S
- 2020
- Published
A Discriminative Latent-Variable Model for Bilingual Lexicon Induction
Ruder, S., Cotterell, R., Kementchedjhieva, Yova Radoslavova & Søgaard, Anders, 2020, Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, p. 458–468Research 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
DaNE: A named entity resource for danish
Hvingelby, R., Pauli, A. B., Barrett, M., Rosted, C., Lidegaard, L. M. & Søgaard, Anders, 2020, LREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings. Calzolari, N., Bechet, F., Blache, P., Choukri, K., Cieri, C., Declerck, T., Goggi, S., Isahara, H., Maegaard, B., Mariani, J., Mazo, H., Moreno, A., Odijk, J. & Piperidis, S. (eds.). European Language Resources Association (ELRA), p. 4597-4604Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Do end-to-end speech recognition models care about context?
Borgholt, L., Havtorn, J. D., Agic, Ž., Søgaard, Anders, Maaløe, L. & Igel, Christian, 2020, Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH. International Speech Communication Association (ISCA), Vol. 2020-October. p. 4352-4356Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Grammatical Error Correction in Low Error Density Domains: A New Benchmark and Analyses
Flachs, S. H., Lacroix, O., Yannakoudakis, H., Rei, M. & Søgaard, Anders, 2020, Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). Association for Computational Linguistics, p. 8467–8478Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Model-based annotation of coreference
Aralikatte, R. & Søgaard, Anders, 2020, LREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings. Calzolari, N., Bechet, F., Blache, P., Choukri, K., Cieri, C., Declerck, T., Goggi, S., Isahara, H., Maegaard, B., Mariani, J., Mazo, H., Moreno, A., Odijk, J. & Piperidis, S. (eds.). European Language Resources Association (ELRA), p. 74-79Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Neural Speed Reading Audited
Søgaard, Anders, 2020, Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, p. 148–153Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Parameter sharing between dependency parsers for related languages
Lhoneux, M. D., Bjerva, J., Augenstein, Isabelle & Søgaard, Anders, 2020, Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing . Association for Computational Linguistics, p. 4992-4997Research 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
ID: 13266
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489
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Multilingual projection for parsing truly low resource languages
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353
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Multi-task Learning of Pairwise Sequence Classification Tasks Over Disparate Label Spaces
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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322
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Reading metrics for estimating task efficiency with MT output
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Published