Isabelle Augenstein
Professor
- 2020
- Udgivet
- Udgivet
Unsupervised Discovery of Gendered Language through Latent-Variable Modeling
Hoyle, A. M., Wolf-sonkin, L., Wallach, H., Augenstein, Isabelle & Cotterell, R., 2020, Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, s. 1706-1716Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
Multi-Sense Language Modelling
Lekkas, A., Schneider-Kamp, P. & Augenstein, Isabelle, 2020, I: arXiv. CyRR 2020, 10 s.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning
- Udgivet
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, s. 4992-4997Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
Unsupervised Evaluation for Question Answering with Transformers
Muttenthaler, L., Augenstein, Isabelle & Bjerva, J., 2020, Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP. Association for Computational Linguistics, s. 83-90Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
Zero-Shot Cross-Lingual Transfer with Meta Learning
Nooralahzadeh, F., Bekoulis, G., Bjerva, J. & Augenstein, Isabelle, 2020, Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). Association for Computational Linguistics, s. 4547-4562Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
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. (red.). PMLR, s. 440-449 (Proceedings of Machine Learning Research, Bind 124).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
What Can We Do to Improve Peer Review in NLP?
Rogers, A. & Augenstein, Isabelle, 2020, Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, s. 1256-1262Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
Disembodied Machine Learning: On the Illusion of Objectivity in NLP
Waseem, Z., Lulz, S., Bingel, J. & Augenstein, Isabelle, 2020, I: OpenReview.net. 7 s.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning
- Udgivet
Claim Check-Worthiness Detection as Positive Unlabelled Learning
Wright, Dustin & Augenstein, Isabelle, 2020, Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, s. 476-488Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
ID: 180388519
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Mapping (Dis-)Information Flow about the MH17 Plane Crash
Publikation: Konferencebidrag › Paper › Forskning
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Multi-task Learning of Pairwise Sequence Classification Tasks Over Disparate Label Spaces
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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Proceedings of the 4th Workshop on Representation Learning for NLP (RepL4NLP-2019)
Publikation: Bog/antologi/afhandling/rapport › Bog › Forskning › fagfællebedømt
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