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Results: 10
Number of items: 10
  • Open Access
    Bavaresco, A., de Heer Kloots, M., Pezzelle, S., & Fernández, R. (2026). Vision-Language Models Align with Human Neural Representations in Concept Processing. In V. Demberg, K. Inui, & L. Marquez (Eds.), The 19th Conference of the European Chapter of the Association for Computational Linguistics : proceedings of the conference: EACL 2026 : March 24-29, 2026 (Vol. 1, pp. 3255-3274). Association for Computational Linguistics. https://doi.org/10.48550/arXiv.2407.17914, https://doi.org/10.18653/v1/2026.eacl-long.150
  • Open Access
    Benjamin, A. S., Beyer, A.-L., de Heer Kloots, M., Hwang, J., Karoui, H., Ostrow, M., Rubruck, J., Sandbrink, K., Grant, S., Saxe, A., & McClelland, J. L. (2026). An Introduction to Connectionist Theories of Semantic Cognition. Proceedings of Machine Learning Research, 320, 42-67. https://proceedings.mlr.press/v320/benjamin26a.html
  • Bavaresco, A., de Heer Kloots, M., Pezzelle, S., & Fernández, R. (2025, April 15). Modelling Multimodal Integration in Human Concept Processing with Vision-Language Models [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15221180
  • Open Access
    Suijkerbuijk, M., Prins, Z., de Heer Kloots, M., Zuidema, W., & Frank, S. L. (2025). BLiMP-NL: A Corpus of Dutch Minimal Pairs and Acceptability Judgments for Language Model Evaluation. Computational Linguistics, 51(4), 1267-1301. https://doi.org/10.31234/osf.io/mhjbx_v2, https://doi.org/10.1162/COLI_a_00559
  • Open Access
    de Heer Kloots, M., Mohebbi, H., Pouw, C., Shen, G., Zuidema, W., & Bentum, M. (2025). What do self-supervised speech models know about Dutch? Analyzing advantages of language-specific pre-training. Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, 26, 256-260. https://doi.org/10.48550/arXiv.2506.00981, https://doi.org/10.21437/Interspeech.2025-1526
  • Suijkerbuijk, M., Prins, Z., de Heer Kloots, M. L. S., Zuidema, W. H., & Frank, S. (2025). BLiMP-NL: The Benchmark of Linguistic Minimal Pairs for Dutch [Data set]. Radboud Universiteit. https://doi.org/10.34973/tj4p-y007
  • de Heer Kloots, M., Mohebbi, H., Pouw, C., Shen, G., Zuidema, W., & Bentum, M. (2025, May 29). SSL-NL dataset [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15548946
  • Open Access
    de Heer Kloots, M., & Zuidema, W. (2024). Human-like Linguistic Biases in Neural Speech Models: Phonetic Categorization and Phonotactic Constraints in Wav2Vec2.0. Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, 25, 4593-4597. https://doi.org/10.21437/Interspeech.2024-2490
  • 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
    Jumelet, J., Hanna, M., de Heer Kloots, M., Langedijk, A., Pouw, C., & van der Wal, O. (2023). ChapGTP, ILLC’s Attempt at Raising a BabyLM: Improving Data Efficiency by Automatic Task Formation. In A. Warstadt, A. Mueller, L. Choshen, E. Wilcox, C. Zhuang, J. Ciro, R. Mosquera, B. Paranjabe, A. Williams, T. Linzen, & R. Cotterell (Eds.), Findings of the BabyLM Challenge: Sample-efficient pretraining on developmentally plausible corpora (pp. 74-85). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.conll-babylm.6
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