Isabelle Augenstein
Professor
- 2023
- Udgivet
Introduction to the Special Issue on Truth and Trust Online
Wright, Dustin, Papotti, P. & Augenstein, Isabelle, 2023, I: Journal of Data and Information Quality. 15, 1, 1.Publikation: Bidrag til tidsskrift › Leder › Forskning
- Udgivet
Invisible Women in Digital Diplomacy: A Multidimensional Framework for Online Gender Bias Against Women Ambassadors Worldwide
Golovchenko, Yevgeniy, Stanczak, Karolina Ewa, Adler-Nissen, Rebecca, Wangen, P. & Augenstein, Isabelle, 2023, arxiv.org, 59 s.Publikation: Working paper › Preprint › Forskning
- 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
Measuring Intersectional Biases in Historical Documents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
Multilingual Event Extraction from Historical Newspaper Adverts
Borenstein, Nadav, Da Silva Perez, N. & Augenstein, Isabelle, 2023, Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics: Long Papers. Association for Computational Linguistics (ACL), Bind 1. s. 10304-10325Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
PHD: Pixel-Based Language Modeling of Historical Documents
Borenstein, Nadav, Rust, Phillip, Elliott, Desmond & Augenstein, Isabelle, 2023, Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processin. Association for Computational Linguistics (ACL), s. 87–107Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
People Make Better Edits: Measuring the Efficacy of LLM-Generated Counterfactually Augmented Data for Harmful Language Detection
Sen, I., Assenmacher, D., Samory, M., Augenstein, Isabelle, Aalst, W. & Wagner, C., 2023, Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (ACL), s. 10480-10504Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
Preface: Special issue on NLP approaches to offensive content online
Zampieri, M., Augenstein, Isabelle, Krishnan, S., Melton, J. & Nakov, P., 2023, I: Natural Language Engineering. 29, 6, s. 1415 1 s.Publikation: Bidrag til tidsskrift › Leder › Forskning
- Udgivet
Probing Pre-Trained Language Models for Cross-Cultural Differences in Values
Arora, Arnav, Kaffee, L. & Augenstein, Isabelle, 2023, Proceedings of the First Workshop on Cross-Cultural Considerations in NLP (C3NLP). Association for Computational Linguistics (ACL), s. 114-130Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehension
Rogers, Anna, Gardner, M. & Augenstein, Isabelle, 2023, I: ACM Computing Surveys. 55, 10, 45 s., 197.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
ID: 180388519
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1525
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Mapping (Dis-)Information Flow about the MH17 Plane Crash
Publikation: Konferencebidrag › Paper › Forskning
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353
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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
Udgivet -
236
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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