Isabelle Augenstein

Isabelle Augenstein

Professor

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    ORCID: 0000-0003-1562-7909

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    1. Published

      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

    2. Published

      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

    3. Published

      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

    4. Published

      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. 78–93

      Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

    5. Published

      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. 1620–1635

      Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

    6. Published

      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

    7. Published

      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. 11670–11688

      Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

    8. Published

      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. 4547-4562

      Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

    9. Published

      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. 83-90

      Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

    10. Published

      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. 122-129

      Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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