Isabelle Augenstein
Professor
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Issue Framing in Online Discussion Fora
Hartmann, M., Jansen, T., Augenstein, Isabelle & Søgaard, Anders, 2019, Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Association for Computational Linguistics, p. 1401-1407Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Mapping (Dis-)Information Flow about the MH17 Plane Crash
Hartmann, M., Golovchenko, Yevgeniy & Augenstein, Isabelle, 2019, p. 45-55.Research output: Contribution to conference › Paper › Research
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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 p. (CEUR Workshop Proceedings).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research
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Revisiting Softmax for Uncertainty Approximation in Text Classification
Holm, Andreas Nugaard, Wright, Dustin & Augenstein, Isabelle, 2023, In: Information (Switzerland). 14, 7, 16 p., 420.Research output: Contribution to journal › Journal article › Research › peer-review
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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, In: Information Fusion. 79, p. 263-278 16 p.Research output: Contribution to journal › Journal article › Research › peer-review
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Combining Sentiment Lexica with a Multi-View Variational Autoencoder
Hoyle, A. M., Wolf-sonkin, L., Wallach, H., Cotterell, R. & Augenstein, Isabelle, 2019, Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Association for Computational Linguistics, p. 635-640Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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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, p. 1706-1716Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Generating Fluent Fact Checking Explanations with Unsupervised Post-Editing
Jolly, S., Atanasova, Pepa Kostadinova & Augenstein, Isabelle, 2022, In: Information (Switzerland). 13, 10, p. 1-18 500.Research output: Contribution to journal › Journal article › Research › peer-review
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Thorny Roses: Investigating the Dual Use Dilemma in Natural Language Processing
Kaffee, L., Arora, Arnav, Talat, Z. & Augenstein, Isabelle, 2023, Findings of the Association for Computational Linguistics: EMNLP 2023. Association for Computational Linguistics (ACL), p. 13977-13998Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Why Should This Article Be Deleted? Transparent Stance Detection in Multilingual Wikipedia Editor Discussions
Kaffee, L., Arora, Arnav & Augenstein, Isabelle, 2023, Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (ACL), p. 5891-5909Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Character-level Supervision for Low-resource POS Tagging
Kann, K., Bjerva, J., Augenstein, Isabelle, Plank, B. & Søgaard, Anders, 2018, Proceedings of the Workshop on Deep Learning Approaches for Low-Resource NLP. Association for Computational Linguistics, p. 1–11Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Copenhagen at CoNLL–SIGMORPHON 2018: Multilingual Inflection in Context with Explicit Morphosyntactic Decoding
Kementchedjhieva, Yova Radoslavova, Bjerva, J. & Augenstein, Isabelle, 2018, Proceedings of the CoNLL SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection . Association for Computational Linguistics, p. 93–98Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Multi-Sense Language Modelling
Lekkas, A., Schneider-Kamp, P. & Augenstein, Isabelle, 2020, In: arXiv. CyRR 2020, 10 p.Research output: Contribution to journal › Journal article › Research
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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, p. 4992-4997Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Quantifying gender biases towards politicians on Reddit
Marjanovic, Sara Vera, Stanczak, Karolina Ewa & Augenstein, Isabelle, 2022, In: PLoS ONE. 17, 10 October, p. 1-36 e0274317.Research output: Contribution to journal › Journal article › Research › peer-review
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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), p. 146-154 9 p.Research 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
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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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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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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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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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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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Long-Tail Zero and Few-Shot Learning via Contrastive Pretraining on and for Small Data
Rethmeier, Nils & Augenstein, Isabelle, 2022, In: Computer Sciences & Mathematics Forum . 3, 18 p., 10.Research output: Contribution to journal › Journal article › 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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A Primer on Contrastive Pretraining in Language Processing: Methods, Lessons Learned, and Perspectives
Rethmeier, Nils & Augenstein, Isabelle, 2023, In: ACM Computing Surveys. 55, 10, 17 p., 203.Research output: Contribution to journal › Journal article › 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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QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehension
Rogers, Anna, Gardner, M. & Augenstein, Isabelle, 2023, In: ACM Computing Surveys. 55, 10, 45 p., 197.Research output: Contribution to journal › Journal article › Research › peer-review
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Learning what to share between loosely related tasks
Ruder, S., Bingel, J., Augenstein, Isabelle & Søgaard, Anders, 23 May 2017, In: arXiv.Research output: Contribution to journal › Journal article › Research
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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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A Neighborhood Framework for Resource-Lean Content Flagging
Sarwar, S. M., Zlatkova, D., Hardalov, M., Dinkov, Y., Augenstein, Isabelle & Nakov, P., 2022, In: Transactions of the Association for Computational Linguistics. 10, p. 484-502Research output: Contribution to journal › Journal article › 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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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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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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White Paper - Creating a Repository of Objectionable Online Content: Addressing Undesirable Biases and Ethical Considerations
Solorio, T., Shafaei, M., Smailis, C., Augenstein, Isabelle, Mitchell, M., Stapf, I. & Kakadiaris, I., 2021, In: OpenReview.net. 5 p.Research output: Contribution to journal › Journal article › Research
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Grammatical Gender's Influence on Distributional Semantics: A Causal Perspective
Stanczak, Karolina Ewa, Du, K., Williams, A., Augenstein, Isabelle & Cotterell, R., 2023, arxiv.org, 12 p.Research output: Working paper › Preprint › Research
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A Latent-Variable Model for Intrinsic Probing
Stanczak, Karolina Ewa, Torroba Hennigen, L., Williams, A., Cotterell, R. & Augenstein, Isabelle, 2023, In: AAAI Conference on Artificial Intelligence. 37, 11, p. 13591-13599Research output: Contribution to journal › Journal article › Research › peer-review
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A Latent-Variable Model for Intrinsic Probing
Stanczak, Karolina Ewa, Hennigen, L. T., Williams, A., Cotterell, R. & Augenstein, Isabelle, 20 Jan 2022, arxiv.org, 15 p.Research output: Working paper › Preprint › Research
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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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Quantifying gender bias towards politicians in cross-lingual language models
Stanczak, Karolina Ewa, Choudhury, S. R., Pimentel, T., Cotterell, R. & Augenstein, Isabelle, 2023, In: PLoS ONE. 18, 11 November, p. 1-24 e0277640.Research output: Contribution to journal › Journal article › 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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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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Disembodied Machine Learning: On the Illusion of Objectivity in NLP
Waseem, Z., Lulz, S., Bingel, J. & Augenstein, Isabelle, 2020, In: OpenReview.net. 7 p.Research output: Contribution to journal › Journal article › 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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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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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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Introduction to the Special Issue on Truth and Trust Online
Wright, Dustin, Papotti, P. & Augenstein, Isabelle, 2023, In: Journal of Data and Information Quality. 15, 1, 1.Research output: Contribution to journal › Editorial › Research
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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
ID: 180388519
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Mapping (Dis-)Information Flow about the MH17 Plane Crash
Research output: Contribution to conference › Paper › Research
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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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Proceedings of the 4th Workshop on Representation Learning for NLP (RepL4NLP-2019)
Research output: Book/Report › Book › Research › peer-review
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