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Selected publications of Yair Lakretz
Articles in journals
  1. Théo Desbordes, Yair Lakretz, Valérie Chanoine, Maxime Oquab, Jean-Michel Badier, Agnès Trébuchon, Romain Carron, Christian-G Bénar, Stanislas Dehaene, and Jean-Rémi King. Dimensionality and ramping: Signatures of sentence integration in the dynamics of brains and deep language models. Journal of Neuroscience, 2023. [WWW]


  2. Alexandre Pasquiou, Yair Lakretz, Bertrand Thirion, and Christophe Pallier. Information-Restricted Neural Language Models Reveal Different Brain Regions’ Sensitivity to Semantics, Syntax, and Context. Neurobiology of Language, 4(4):611--636, December 2023. [WWW] [PDF] [Abstract]


  3. Stanislas Dehaene, Fosca Al Roumi, Yair Lakretz, Samuel Planton, and Mathias Sablé-Meyer. Symbols and mental programs: a hypothesis about human singularity. Trends in Cognitive Sciences, 2022. [PDF]


  4. Christos-Nikolaos Zacharopoulos, Stanislas Dehaene, and Yair Lakretz. Disentangling Hierarchical and Sequential Computations during Sentence Processing. bioRxiv, pp 2022--07, 2022. [WWW]


  5. Yair Lakretz, Theo Desbordes, Dieuwke Hupkes, and Stanislas Dehaene. Causal transformers perform below chance on recursive nested constructions, unlike humans. arXiv preprint arXiv:2110.07240, 2021.


  6. Yair Lakretz, Théo Desbordes, Jean-Rémi King, Benoît Crabbé, Maxime Oquab, and Stanislas Dehaene. Can RNNs learn Recursive Nested Subject-Verb Agreements?. arXiv preprint arXiv:2101.02258, 2021. [WWW] [PDF]


  7. Yair Lakretz, Dieuwke Hupkes, Alessandra Vergallito, Marco Marelli, Marco Baroni, and Stanislas Dehaene. Mechanisms for handling nested dependencies in neural-network language models and humans. Cognition, pp 104699, 2021. [WWW]


  8. Yair Lakretz, Stanislas Dehaene, and Jean-Rémi King. What Limits Our Capacity to Process Nested Long-Range Dependencies in Sentence Comprehension?. Entropy, 22(4):446, 2020.


  9. Yair Lakretz, Dieuwke Hupkes, Alessandra Vergallito, Marco Marelli, Marco Baroni, and Stanislas Dehaene. Exploring processing of nested dependencies in neural-network language models and humans. arXiv preprint arXiv:2006.11098, 2020.


  10. Oscar Woolnough, Cristian Donos, Patrick S Rollo, Kiefer J Forseth, Yair Lakretz, Nathan E Crone, Simon Fischer-Baum, Stanislas Dehaene, and Nitin Tandon. Spatiotemporal dynamics of orthographic and lexical processing in the ventral visual pathway. Nature Human Behaviour, pp 1--10, 2020. [PDF]


  11. Yair Lakretz, German Kruszewski, Theo Desbordes, Dieuwke Hupkes, Stanislas Dehaene, and Marco Baroni. The emergence of number and syntax units in LSTM language models. arXiv preprint arXiv:1903.07435, 2019. [PDF]


Conference proceedings
  1. Yair Lakretz, Théo Desbordes, Dieuwke Hupkes, and Stanislas Dehaene. Can Transformers Process Recursive Nested Constructions, Like Humans?. In Proceedings of the 29th International Conference on Computational Linguistics, pages 3226--3232, 2022. [WWW]


  2. Alexandre Pasquiou, Yair Lakretz, John T. Hale, Bertrand Thirion, and Christophe Pallier. Neural Language Models are not Born Equal to Fit Brain Data, but Training Helps. In Proceedings of the 39th International Conference on Machine Learning, pages 17499--17516, June 2022. PMLR. [WWW] [PDF] [Abstract]


  3. Yair Lakretz, German Kruszewski, Theo Desbordes, Dieuwke Hupkes, Stanislas Dehaene, and Marco Baroni. The emergence of number and syntax units in LSTM language models. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), Minneapolis, Minnesota, pages 11--20, June 2019. Association for Computational Linguistics. [WWW] [PDF] [Abstract]



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