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Results: 102
Number of items: 102
  • Open Access
    Fresen, A. J., Choenni, R., Heilbron, M., Zuidema, W., & de Heer Kloots, M. (2024). Language Models That Accurately Represent Syntactic Structure Exhibit Higher Representational Similarity To Brain Activity. In L. Samuelson, S. Frank, M. Toneva, A. Mackey, & E. Hazeltine (Eds.), 46th Annual Meeting of the Cognitive Science Society (CogSci 2024): Dynamics of Cognition : Rotterdam, the Netherlands, 24-27 July 2024 (Vol. 2, pp. 675-683). (Proceedings of the Annual Meeting of the Cognitive Science Society; Vol. 46). Cognitive Science Society. https://escholarship.org/uc/item/1fp7m6nf
  • Open Access
    Cornelissen, B. J. M. (2024). Measuring musics: Notes on modes, motifs, and melodies. [Thesis, fully internal, Universiteit van Amsterdam].
  • Bockting, C. L., van Dis, E. A. M., van Rooij, R., Zuidema, W., & Bollen, J. (2023). Living guidelines for generative AI - why scientists must oversee its use. Nature, 622(7984), 693-696. https://doi.org/10.1038/d41586-023-03266-1
  • van Dis, E. A. M., Bollen, J., van Rooij, R., Zuidema, W., & Bockting, C. L. (2023). ChatGPT: Five priorities for research. Nature, 614(7947), 223-226. https://doi.org/10.1038/d41586-023-00288-7
  • 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
    Chintam, A., Beloch, R., Zuidema, W., Hanna, M., & van der Wal, O. (2023). Identifying and Adapting Transformer-Components Responsible for Gender Bias in an English Language Model. In Y. Belinkov, S. Hao, J. Jumelet, N. Kim, A. McCarthy, & H. Mohebbi (Eds.), BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP: Proceedings of the Sixth Workshop : EMNLP 2023 : December 7, 2023 (pp. 379-394). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.blackboxnlp-1.29
  • Open Access
    Vélez Vásquez, M. A., Baelemans, M., Driedger, J., Zuidema, W., & Burgoyne, J. A. (2023). Quantifying the ease of playing song chords on the guitar. In A. Sarti, F. Antonacci, M. Sandler, P. Bestagini, S. Dixon, B. Liang, G. Richard, & J. Pauwels (Eds.), Proceedings of the 24th International Society for Music Information Retrieval Conference: Milan, Italy, November 5-9, 2023 (pp. 725-732). ISMIR. https://doi.org/10.5281/zenodo.10265391
  • 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
    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
    Abnar, S. (2023). Inductive biases for learning natural language. [Thesis, fully internal, Universiteitsbibliotheek].
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