Isabelle Augenstein

Isabelle Augenstein

Professor

Member of:


    1. Published

      Retrieval-based goal-directed dialogue generation

      Gonzalez, Ana Valeria, Augenstein, Isabelle & Søgaard, Anders, 2019. 11 p.

      Research output: Contribution to conferencePaperResearch

    2. Published

      Retrieval-based Goal-Oriented Dialogue Generation

      Gonzalez, Ana Valeria, Augenstein, Isabelle & Søgaard, Anders, 2020. 11 p.

      Research output: Contribution to conferencePaperResearch

    3. Published

      Proceedings of The Third Workshop on Representation Learning for NLP

      Augenstein, Isabelle (ed.), Cao, K. (ed.), He, H. (ed.), Hill, F. (ed.), Gella, S. (ed.), Kiros, J. (ed.), Mei, H. (ed.) & Misra , D., 2018, Proceedings of the Third Workshop: Representation Learning for NLP. Association for Computational Linguistics, 224 p.

      Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    4. Published

      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), p. 114-130

      Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    5. Published

      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. 10480-10504

      Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    6. Published

      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. 4992-4997

      Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    7. Published

      PHD: Pixel-Based Language Modeling of Historical Documents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), p. 87–107

      Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    8. Published

      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. 25–29

      Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    9. 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 proceedingArticle in proceedingsResearchpeer-review

    10. Published

      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), Vol. 1. p. 10304-10325

      Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    ID: 180388519