Search results

  • Full text

  • Document type

    • Publication year

  • Organisation

Results: 13
Number of items: 13
  • 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
  • Open Access
    de Heer Kloots, M., Boersma, P., & Zuidema, W. (2026). Linguists should learn to love speech-based deep learning models. Behavioral and Brain Sciences, 49, Article e206. https://doi.org/10.1017/S0140525X26104713, https://doi.org/10.48550/arXiv.2512.14506
  • Open Access
    Styger, S. A., de Heer Kloots, M., van der Wal, O., & Russo, F. (2026). Why are human epistemic agents not displaced in machine learning scientific inquiries? A practice perspective on ML in science. In J. M. Durán, & G. Pozzi (Eds.), Philosophy of Science for Machine Learning: Core Issues and New Perspectives (pp. 315-337). (Synthese Library; Vol. 527). Springer. https://doi.org/10.1007/978-3-032-03083-2_15
  • Open Access
    Sauter, A., Zuidema, W., & de Heer Kloots, M. (2026). The Curious Case of Visual Grounding: Different Effects for Speech-and Text-Based Language Encoders. In ICASSP 2026 - 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP): proceedings : 4-8 May 2026, Barcelona, Spain (pp. 17917-17921). IEEE. https://doi.org/10.48550/arXiv.2509.15837, https://doi.org/10.1109/ICASSP55912.2026.11463880
  • 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
  • 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., 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
  • 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
Page 1 of 2