Searchable List of Research Output

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  • Jimenez-Buedo, M., Russo, F. (2017) Causality and Modelling in the Sciences: Introduction.
    Disputatio, Vol. 9 (pp 423-427)
  • Jimenez-Buedo, M., Russo, F. (2017) Causality and modelling.
    Disputatio, Vol. 9 (pp 423-690)
  • Jimenez-Buedo, M., Russo, F. (2021) Experimental practices and objectivity in the social sciences: re‐embedding construct validity in the internal–external validity distinction.
    Synthese, Vol. 199 (pp 9549-9579)
  • Johnson, R.B., Russo, F., Schoonenboom, J. (2019) Causality in mixed methods research: the meeting of philosophy, science, and practice.
    Journal of Mixed Methods Research, Vol. 13 (pp 143-162)
  • Jolly, S., Pezzelle, S., Nabi, M. (2021) EaSe: A Diagnostic Tool for VQA Based on Answer Diversity.
    In Toutanova, K. Rumshisky, A. Zettlemoyer, L. Hakkani-Tur, D. Beltagy, I. Bethard, S. Cotterell, R. Chakraborty, T. Zhou, Y. (Eds.), The 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: NAACL-HLT 2021 : proceedings of the conference : June 6-11, 2021 (pp 2407-2414). The Association for Computational Linguistics.
  • Jones, Max, Schoonen, T. (2018) Embodied Constraints on Imagination.
    Junkyard of the Mind blog.
    Web publication or website | UvA-DARE
  • Jongsma, M.A., Desain, P., Honing, H. (2004) Rhythmic context influences the auditory evoked potentials of musicians and nonmusicians.
    Biological Psychology, Vol. 66 (pp 129-152)
  • Jongsma, M.L.A., Eichele, T., Quian Quiroga, R., Desain, P., Honing, H. (2005) The effect of expectancy on ommision evoked potentials (OEPs) in musicians and nonmusicians.
    Psychophysiology, Vol. 42 (pp 191-201)
  • Joosten, J.J. (2006) Credit cards, computationele complexiteit en consistentie uitspraken.
    Technical Report. Institute for Logic, Language and Computation.
    Working paper | UvA-DARE
  • Joosten, J.J. (2006) Semantics for sub-intuitionistic logics..
    Preprint Publication Series. Institute for Logic, Language and Computation.
    Working paper | UvA-DARE
  • Joosten, J.J. (2007) Propositional Proof Systems and Fast Consistency Provers.
    Notre Dame Journal of Formal Logic, Vol. 48 (pp 381-398)
    Article | UvA-DARE
  • Joosten, J.J. (2007) Lowerbounds in Proof Complexity.
    The Bulletin of Symbolic Logic, Vol. 13 (pp 263-263)
    Article | UvA-DARE
  • Ju, F., Grilletti, G. (2017) A Dynamic Approach to Temporal Normative Logic.
    In Baltag, A. Seligman, J. Yamada, T. (Eds.), Logic, Rationality, and Interaction: 6th International Workshop, LORI 2017, Sapporo, Japan, September 11-14, 2017 : proceedings (pp 512-525) (Lecture Notes in Computer Science
    FoLLI Publications on Logic, Language and Information, Vol. 10455). Springer.
  • Jumelet, J., Denić, M., Szymanik, J., Hupkes, D., Steinert-Threlkeld, S. (2021) Language models use monotonicity to assess NPI licensing.
    In Zong, C. Xia, F. Li, W. Navigli, R. (Eds.), Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021: Findings of ACL: ACL-IJCNLP 2021 : August 1-6, 2021 (pp 4958–4969). The Association for Computational Linguistics.
  • 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 Warstadt, A. Mueller, A. Choshen, L. Wilcox, E. Zhuang, C. Ciro, J. Mosquera, R. Paranjabe, B. Williams, A. Linzen, T. Cotterell, R. (Eds.), Findings of the BabyLM Challenge: Sample-efficient pretraining on developmentally plausible corpora (pp 74-85). Association for Computational Linguistics.
  • Jumelet, J., Hupkes, D. (2018) Do Language Models Understand Anything? On the Ability of LSTMs to Understand Negative Polarity Items.
    In Linzen, T. Chrupała, G. Alishahi, A. (Eds.), The 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP: EMNLP 2018 : proceedings of the First Workshop : November 1, 2018, Brussels, Belgium (pp 222-231). The Association for Computational Linguistics.
    Conference contribution | https://doi.org/10.18653/v1/W18-5424 | UvA-DARE
  • Jumelet, J., Zuidema, W., Hupkes, D. (2019) Analysing Neural Language Models: Contextual Decomposition Reveals Default Reasoning in Number and Gender Assignment.
    In Bansal, M. Villavicencio, A. (Eds.), The 23rd Conference on Computational Natural Language Learning: CoNLL 2019 : proceedings of the conference : November 3-4, 2019, Hong Kong, China (pp 1-11). The Association for Computational Linguistics.
    Conference contribution | https://doi.org/10.18653/v1/K19-1001 | UvA-DARE
  • Jumelet, J., Zuidema, W. (2023) Feature Interactions Reveal Linguistic Structure in Language Models.
    In Rogers, A. Boyd-Graber, J. Okazaki, N. (Eds.), Findings of the Association for Computational Linguistics: ACL 2023: July 9-14, 2023 (pp 8697–8712). Association for Computational Linguistics.
  • Jumelet, J., Zuidema, W. (2023) Transparency at the Source: Evaluating and Interpreting Language Models With Access to the True Distribution.
    In Bouamor, H. Pino, J. Bali, K. (Eds.), The 2023 Conference on Empirical Methods in Natural Language Processing : Findings of the Association for Computational Linguistics: EMNLP 2023: December 6-10, 2023 (pp 4354–4369). Association for Computational Linguistics.
  • Jumelet, J. (2020) diagNNose: A Library for Neural Activation Analysis.
    In Alishahi, A. Belinkov, Y. Chrupała, G. Hupkes, D. Pinter, Y. (Eds.), Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP: BlackboxNLP2020 (pp 342-350). The Association for Computational Linguistics.

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