Isabelle Augenstein
Professor
- Udgivet
Measuring Intersectional Biases in Historical Documents
Borenstein, Nadav, Stanczak, Karolina Ewa, Rolskov, T., da Silva Perez, N., Klein Kafer, Natacha & Augenstein, Isabelle, 2023, Findings of the 61st Annual Meeting of the Association for Computational Linguistics, ACL 2023. Association for Computational Linguistics (ACL), Bind ACL 2023. s. 2711–2730Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
Measuring Gender Bias in West Slavic Language Models
Martinková, S., Stańczak, K. & Augenstein, Isabelle, 2023, EACL 2023 - 9th Workshop on Slavic Natural Language Processing, Proceedings of the SlavicNLP 2023. Association for Computational Linguistics (ACL), s. 146-154 9 s.Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
Mapping (Dis-)Information Flow about the MH17 Plane Crash
Hartmann, M., Golovchenko, Yevgeniy & Augenstein, Isabelle, 2019, s. 45-55.Publikation: Konferencebidrag › Paper › Forskning
- Udgivet
Machine Reading, Fast and Slow: When Do Models “Understand” Language?
Ray Choudhury, S., Rogers, Anna & Augenstein, Isabelle, 2022, Proceedings of the 29th International Conference on Computational Linguistics. Association for Computational Linguistics (ACL), s. 78–93Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
Longitudinal Citation Prediction using Temporal Graph Neural Networks
Holm, Andreas Nugaard, Plank, B., Wright, Dustin & Augenstein, Isabelle, 2022, Proceedings of the Workshop on Scientific Document Understanding co-located with 36th AAAI Conference on Artificial Inteligence (AAAI 2022). CEUR, 8 s. (CEUR Workshop Proceedings).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning
- Udgivet
Long-Tail Zero and Few-Shot Learning via Contrastive Pretraining on and for Small Data
Rethmeier, Nils & Augenstein, Isabelle, 2022, I: Computer Sciences & Mathematics Forum . 3, 18 s., 10.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
- Udgivet
Learning what to share between loosely related tasks
Ruder, S., Bingel, J., Augenstein, Isabelle & Søgaard, Anders, 23 maj 2017, I: arXiv.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning
- Udgivet
Latent Multi-Task Architecture Learning
Ruder, S., Bingel, J., Augenstein, Isabelle & Søgaard, Anders, 2019, Proceedings of 33nd AAAI Conference on Artificial Intelligence, AAAI 2019. AAAI Press, s. 4822-4829Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
Joint emotion label space modeling for affect lexica
De Bruyne, L., Atanasova, Pepa Kostadinova & Augenstein, Isabelle, jan. 2022, I: Computer Speech and Language. 71, 20 s., 101257.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
- Udgivet
Joint Emotion Label Space Modelling for Affect Lexica
De Bruyne, L., Atanasova, Pepa Kostadinova & Augenstein, Isabelle, 2019, I: arXiv.org. CoRR 2019, 24 s.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning
ID: 180388519
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Mapping (Dis-)Information Flow about the MH17 Plane Crash
Publikation: Konferencebidrag › Paper › Forskning
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343
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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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228
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Proceedings of the 4th Workshop on Representation Learning for NLP (RepL4NLP-2019)
Publikation: Bog/antologi/afhandling/rapport › Bog › Forskning › fagfællebedømt
Udgivet