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Results: 106
Number of items: 106
  • Open Access
    Langedijk, A., Mohebbi, H., Sarti, G., Zuidema, W., & Jumelet, J. (2024). DecoderLens: Layerwise Interpretation of Encoder-Decoder Transformers. In K. Duh, H. Gomez, & S. Bethard (Eds.), Findings of the Association for Computational Linguistics: NAACL 2024: Findings: Findings 2024 : June 16-21, 2024 (pp. 4764-4780). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.findings-naacl.296
  • Open Access
    van Sprang, A., Acar, E., & Zuidema, W. (2024). Enforcing Interpretability in Time Series Transformers: A Concept Bottleneck Framework. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2410.06070
  • Open Access
    van der Wal, O., Bachmann, D., Leidinger, A., van Maanen, L., Zuidema, W., & Schulz, K. (2024). Undesirable Biases in NLP: Addressing Challenges of Measurement. Journal of Artificial Intelligence Research, 79, 1-40. https://doi.org/10.1613/jair.1.15195
  • 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
    Bachmann, D., van der Wal, O., Chvojka, E., Zuidema, W. H., van Maanen, L., & Schulz, K. (2024). fl-IRT-ing with Psychometrics to Improve NLP Bias Measurement. Minds and Machines, 34(4), Article 37. https://doi.org/10.1007/s11023-024-09695-9
  • Open Access
    Cornelissen, B. J. M. (2024). Measuring musics: Notes on modes, motifs, and melodies. [Thesis, fully internal, Universiteit van Amsterdam].
  • 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
  • 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
  • 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
    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
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