Isabelle Augenstein
Professor
- 2022
- Udgivet
A Survey on Stance Detection for Mis- and Disinformation Identification
Hardalov, M., Arora, Arnav, Nakov, P. & Augenstein, Isabelle, 2022, Findings of the Association for Computational Linguistics: NAACL 2022 - Findings. Association for Computational Linguistics (ACL), s. 1259-1277Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
Few-Shot Cross-Lingual Stance Detection with Sentiment-Based Pre-Training
Hardalov, M., Arora, Arnav, Nakov, P. & Augenstein, Isabelle, 2022, I: Proceedings of the International Joint Conference on Artificial Intelligence. 36, 10, s. 10729-10737.Publikation: Bidrag til tidsskrift › Konferenceartikel › 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
Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence
Holzinger, A., Dehmer, M., Emmert-Streib, F., Cucchiara, R., Augenstein, Isabelle, Ser, J. D., Samek, W., Jurisica, I. & Díaz-Rodríguez, N., 2022, I: Information Fusion. 79, s. 263-278 16 s.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
- Udgivet
Generating Fluent Fact Checking Explanations with Unsupervised Post-Editing
Jolly, S., Atanasova, Pepa Kostadinova & Augenstein, Isabelle, 2022, I: Information (Switzerland). 13, 10, s. 1-18 500.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
- Udgivet
Quantifying gender biases towards politicians on Reddit
Marjanovic, Sara Vera, Stanczak, Karolina Ewa & Augenstein, Isabelle, 2022, I: PLoS ONE. 17, 10 October, s. 1-36 e0274317.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
- Udgivet
Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings
Ostendorff, M., Rethmeier, Nils, Augenstein, Isabelle, Gipp, B. & Rehm, G., 2022, Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (ACL), s. 11670–11688Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
Can Edge Probing Tests Reveal Linguistic Knowledge in QA Models?
Ray Choudhury, S., Bhutani, N. & Augenstein, Isabelle, 2022, Proceedings of the 29th International Conference on Computational Linguistics. Association for Computational Linguistics (ACL), s. 1620–1635Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- 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
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
ID: 180388519
Flest downloads
-
1507
downloads
Mapping (Dis-)Information Flow about the MH17 Plane Crash
Publikation: Konferencebidrag › Paper › Forskning
Udgivet -
342
downloads
Multi-task Learning of Pairwise Sequence Classification Tasks Over Disparate Label Spaces
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Udgivet -
224
downloads
Proceedings of the 4th Workshop on Representation Learning for NLP (RepL4NLP-2019)
Publikation: Bog/antologi/afhandling/rapport › Bog › Forskning › fagfællebedømt
Udgivet