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Results: 4
Number of items: 4
  • 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
    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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