Anders Søgaard
Professor
Natural Language Processing
Universitetsparken 1
2100 København Ø
Department of Communication
Karen Blixens Plads 8
2300 København S
- Published
When does deep multi-task learning work for loosely related document classification tasks?
Kerinec, E., Søgaard, Anders & Braud, C., 2018, Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP. Association for Computational Linguistics, p. 1-8Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Lost in Evaluation: Misleading Benchmarks for Bilingual Dictionary Induction
Kementchedjhieva, Yova Radoslavova, lwp876, 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. 3336–3341Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Generalizing Procrustes Analysis for Better Bilingual Dictionary Induction
Kementchedjhieva, Yova Radoslavova, Ruder, S., Cotterell, R. & Søgaard, Anders, 2018, Proceedings of the 22nd Conference on Computational Natural Language Learning (CoNLL 2018). Association for Computational Linguistics, p. 211–220Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Dynamic Forecasting of Conversation Derailment
Kementchedjhieva, Yova Radoslavova & Søgaard, Anders, 2021, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, p. 7915–7919Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
John praised Mary because he ? Implicit Causality Bias and Its Interaction with Explicit Cues in LMs
Kementchedjhieva, Yova Radoslavova, Anderson, M. & Søgaard, Anders, 2021, Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. Association for Computational Linguistics, p. 4859-4871Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Grammatical Error Correction through Round-Trip Machine Translation
Kementchedjhieva, Yova Radoslavova & Søgaard, Anders, 2023, Findings of the Association for Computational Linguistics: EACL 2023. Association for Computational Linguistics (ACL), p. 2208-2215Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Copyright Violations and Large Language Models
Karamolegkou, Antonia, Li, Jiaang, Zhou, L. & Søgaard, Anders, 2023, Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (ACL), p. 7403-7412Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Mapping Brains with Language Models: A Survey
Karamolegkou, Antonia, Abdou, M. & Søgaard, Anders, 2023, Findings of the Association for Computational Linguistics: ACL 2023. Association for Computational Linguistics (ACL), p. 9748-9762Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Character-level Supervision for Low-resource POS Tagging
Kann, K., Bjerva, J., Augenstein, Isabelle, Plank, B. & Søgaard, Anders, 2018, Proceedings of the Workshop on Deep Learning Approaches for Low-Resource NLP. Association for Computational Linguistics, p. 1–11Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Weakly Supervised POS Taggers Perform Poorly on Truly Low-Resource Languages
Kann, K., Lacroix, O. & Søgaard, Anders, 2020, Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2020): [AAAI-20 Technical Tracks 5]. AAAI Press, p. 8066-8073.Research 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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