Isabelle Augenstein
Professor
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TempEL: Linking Dynamically Evolving and Newly Emerging Entities
Zaporojets, K., Kaffee, L. F., Deleu, J., Demeester, T., Develder, C. & Augenstein, Isabelle, 2022, Advances in Neural Information Processing Systems 35 (NeurIPS 2022). NeurIPS Proceedings, 17 p. (Advances in Neural Information Processing Systems, Vol. 35).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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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, p. 476-488Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Transformer Based Multi-Source Domain Adaptation
Wright, Dustin & Augenstein, Isabelle, 2020, Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). Association for Computational Linguistics, p. 7963-7974Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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CiteWorth: Cite-Worthiness Detection for Improved Scientific Document Understanding
Wright, Dustin & Augenstein, Isabelle, 2021, Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. Association for Computational Linguistics, p. 1796-1807Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Generating Scientific Claims for Zero-Shot Scientific Fact Checking
Wright, Dustin, Wadden, D., Lo, K., Kuehl, B., Cohan, A., Augenstein, Isabelle & Wang, L. L., 2022, Generating Scientific Claims for Zero-Shot Scientific Fact Checking. Association for Computational LinguisticsResearch output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Semi-Supervised Exaggeration Detection of Health Science Press Releases
Wright, Dustin & Augenstein, Isabelle, 2021, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, p. 10824-10836Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Modeling Information Change in Science Communication with Semantically Matched Paraphrases
Wright, Dustin, Pei, J., Jurgens, D. & Augenstein, Isabelle, 2022, Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, p. 1783-1807 25 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research
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Jack the Reader – A Machine Reading Framework
Weissenborn, D., Minervini, P., Dettmers, T., Augenstein, Isabelle, Welbl, J., Rocktäschel, T., Bošnjak, M., Mitchell, J., Demeester, T., Stenetorp, P. & Riedel, S., 2018, Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics-System Demonstrations. Association for Computational Linguistics, p. 25–30Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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EACL 2023 - 17th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2023
Vlachos, A. (ed.) & Augenstein, Isabelle (ed.), 2023, Findings of the Association for Computational Linguistics: EACL 2023. Association for Computational Linguistics (ACL)Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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EACL 2023 - 17th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference
Vlachos, A. (ed.) & Augenstein, Isabelle (ed.), 2023, EACL 2023 - 17th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference. Association for Computational Linguistics (ACL)Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Nightmare at test time: How punctuation prevents parsers from generalizing
Søgaard, Anders, Lhoneux, M. D. & Augenstein, Isabelle, 2018, Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP . Association for Computational Linguistics, p. 25–29Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Same Neurons, Different Languages: Probing Morphosyntax in Multilingual Pre-trained Models
Stanczak, Karolina Ewa, Ponti, E., Hennigen, L. T., Cotterell, R. & Augenstein, Isabelle, 2022, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Association for Computational Linguistics (ACL), p. 1589-1598Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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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), p. 10480-10504Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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How Does Counterfactually Augmented Data Impact Models for Social Computing Constructs?
Sen, I., Samory, M., Flöck, F., Wagner, C. & Augenstein, Isabelle, 2021, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, p. 325-344Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Counterfactually Augmented Data and Unintended Bias: The Case of Sexism and Hate Speech Detection
Sen, I., Samory, M., Wagner, C. & Augenstein, Isabelle, 2022, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Association for Computational Linguistics (ACL), p. 4716-4726Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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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, p. 4822-4829Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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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, p. 1256-1262Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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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. (eds.). PMLR, p. 440-449 (Proceedings of Machine Learning Research, Vol. 124).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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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), p. 78–93Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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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), p. 1620–1635Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Multi-Hop Fact Checking of Political Claims
Ostrowski, W., Arora, Arnav, Atanasova, Pepa Kostadinova & Augenstein, Isabelle, 2021, Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence, Vol. CoRR 2020. p. 3892-3898 (arXiv.org).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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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), p. 11670–11688Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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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, p. 4547-4562Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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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, p. 83-90Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Is Sparse Attention more Interpretable?
Meister, C., Lazov, S., Augenstein, Isabelle & Cotterell, R., 2021, Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers). Association for Computational Linguistics, p. 122-129Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
ID: 180388519
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1507
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Mapping (Dis-)Information Flow about the MH17 Plane Crash
Research output: Contribution to conference › Paper › Research
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342
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Multi-task Learning of Pairwise Sequence Classification Tasks Over Disparate Label Spaces
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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224
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Proceedings of the 4th Workshop on Representation Learning for NLP (RepL4NLP-2019)
Research output: Book/Report › Book › Research › peer-review
Published