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Results: 70
Number of items: 70
  • Open Access
    Boag, R. J., Innes, R. J., Stevenson, N., Bahg, G., Busemeyer, J. R., Cox, G. E., Donkin, C., Frank, M. J., Hawkins, G. E., Heathcote, A., Hedge, C., Lerche, V., Lilburn, S. D., Logan, G. D., Matzke, D., Miletić, S., Osth, A. F., Palmeri, T. J., Sederberg, P. B., ... Forstmann, B. U. (2025). An Expert Guide to Planning Experimental Tasks For Evidence-Accumulation Modeling. Advances in Methods and Practices in Psychological Science, 8(2), Article 25152459251336127. https://doi.org/10.1177/25152459251336127
  • Open Access
    Ramotowska, S., Marty, P., Van Maanen, L., & Sudo, Y. (2024). Some but not all speakers sometimes but not always derive scalar implicatures. 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. 6, pp. 3931-3938). (Proceedings of the Annual Meeting of the Cognitive Science Society; Vol. 46). Cognitive Science Society. https://escholarship.org/uc/item/1p41114b
  • Open Access
    Bachmann, D., & van Maanen, L. (2024). Towards the application of evidence accumulation models in the design of (semi-)autonomous driving systems – an attempt to overcome the sample size roadblock. International Journal of Human-Computer Studies, 185, Article 103220. https://doi.org/10.1016/j.ijhcs.2024.103220
  • Open Access
    Kolvoort, I. R., Fisher, E. L., van Rooij, R., Schulz, K., & van Maanen, L. (2024). Probabilistic causal reasoning under time pressure. PLoS ONE, 19(4), Article e0297011. https://doi.org/10.1371/journal.pone.0297011
  • 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
    Ramotowska, S., Haaf, J., Van Maanen, L., & Szymanik, J. (2024). Most quantifiers have many meanings. Psychonomic Bulletin & Review, 31(6), 2692-2703. https://doi.org/10.3758/s13423-024-02502-7
  • 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
    Ramotowska, S., Archambeau, K., Augurzky, P., Schlotterbeck, F., Berberyan, H. S., Van Maanen, L., & Szymanik, J. (2024). Testing two-step models of negative quantification using a novel machine learning analysis of EEG. Language, Cognition and Neuroscience, 39(5), 632-656. https://doi.org/10.1080/23273798.2024.2345302
  • Open Access
    van de Pol, I., Lodder, P., van Maanen, L., Steinert-Threlkeld, S., & Szymanik, J. (2023). Quantifiers satisfying semantic universals have shorter minimal description length. Cognition, 232, Article 105150. https://doi.org/10.1016/j.cognition.2022.105150
  • Open Access
    Kolvoort, I. R. (2023). Novel perspectives on the causal mind: Experiments, modeling, and theory. [Thesis, fully internal, Universiteit van Amsterdam].
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