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Results: 106
Number of items: 106
  • Open Access
    Jumelet, J., & Zuidema, W. (2023). Feature Interactions Reveal Linguistic Structure in Language Models. In A. Rogers, J. Boyd-Graber, & N. Okazaki (Eds.), Findings of the Association for Computational Linguistics: ACL 2023: July 9-14, 2023 (pp. 8697–8712). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-acl.554
  • Open Access
    Giulianelli, M. (2023). Neural models of language use: Studies of language comprehension and production in context. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Mohebbi, H., Chrupała, G., Zuidema, W., & Alishahi, A. (2023). Homophone Disambiguation Reveals Patterns of Context Mixing in Speech Transformers. In H. Bouamar, J. Pino, & K. Bali (Eds.), The 2023 Conference on Empirical Methods in Natural Language Processing: EMNLP 2023 : Proceedings of the Conference : December 6-10, 2023 (pp. 8249-8260). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.emnlp-main.513
  • Open Access
    Jumelet, J., & Zuidema, W. (2023). Transparency at the Source: Evaluating and Interpreting Language Models With Access to the True Distribution. In H. Bouamor, J. Pino, & K. Bali (Eds.), The 2023 Conference on Empirical Methods in Natural Language Processing : Findings of the Association for Computational Linguistics: EMNLP 2023: December 6-10, 2023 (pp. 4354–4369). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-emnlp.288
  • Open Access
    Mohebbi, H., Zuidema, W., Chrupała, G., & Alishahi, A. (2023). Quantifying Context Mixing in Transformers. In A. Vlachos, & I. Augenstein (Eds.), The 17th Conference of the European Chapter of the Association for Computational Linguistics: EACL 2023 : proceedings of the conference : May 2-6, 2023 (pp. 3378-3400). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.eacl-main.245
  • Open Access
    Abnar, S. (2023). Inductive biases for learning natural language. [Thesis, fully internal, Universiteitsbibliotheek].
  • Open Access
    van der Wal, O., Jumelet, J., Schulz, K., & Zuidema, W. (2022). The Birth of Bias: A case study on the evolution of gender bias in an English language model. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2207.10245
  • Open Access
    Sinclair, A., Jumelet, J., Zuidema, W., & Fernández, R. (2022). Structural Persistence in Language Models: Priming as a Window into Abstract Language Representations. Transactions of the Association of Computational Linguistics, 10, 1031–1050. https://doi.org/10.1162/tacl_a_00504
  • Open Access
    van der Wal, O., Bachmann, D., Leidinger, A., van Maanen, L., Zuidema, W., & Schulz, K. (2022). Undesirable biases in NLP: Averting a crisis of measurement. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2211.13709
  • Open Access
    Arnoult, S. I. (2021). Adjunction in hierarchical phrase-based translation. [Thesis, fully internal, Universiteit van Amsterdam]. Institute for Logic, Language and Computation.
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