Publications

Lample , G., Zeghidour, N., Usunier, N., Bordes, A. , Denoyer, L. & Ranzato, M. (2017). Fader Networks: Manipulating Images by Sliding Attributes. In NIPS.

Larsen, E., Dupoux, E. & Cristia, A. (2017). Relating unsupervised word segmentation to reported vocabulary acquisition. In INTERSPEECH-2017, 2198-2202. doi:10.21437/Interspeech.2017-937

Le Bars, S., Devaux, A., Nevidal, T., Chambon, V. & Pacherie, E. (2020). Agents' pivotality and reward fairness modulate sense of agency in cooperative joint action. Cognition, 195, 104117. doi:10.1016/j.cognition.2019.104117

Le Clec'H, G., Dehaene, S., Cohen, L., Mehler, J., Dupoux, E., Poline, J., Lehericy, S., van de Moortele, P. & Le Bihan, D. (2000). Distinct cortical areas for names of numbers and body parts independent of language and input modality. Neuroimage, 12(4), 381-391

Le Coënt, A., Fribourg, L., Vacher, J. & Wisniewski, R. (2020). Probabilistic reachability and control synthesis for stochastic switched systems using the tamed Euler method. Nonlinear Analysis: Hybrid Systems, 36, 100860Elsevier. doi:10.1016/j.nahs.2020.100860

Le Godais, G., Linzen, T. & Dupoux, E. (2017). Comparing character-level neural language models using a lexical decision task. In Proceedings of the Conference of the European Chapter of the Association for Computational Linguistics..

Lee, A. , de Gardelle, V. & Mamassian, P. (2021). Global visual confidence. Psychonomic Bulletin and Review, 28, 1233–1242. doi:10.3758/s13423-020-01869-7

Lefebvre, G., Nioche, A., Bourgeois-Gironde, S. & Palminteri, S. (2018). Contrasting temporal difference and opportunity cost reinforcement learning in an empirical money-emergence paradigm. PNAS, 115(49), E11446-E11454. doi:10.1073/pnas.1813197115

Lefebvre, G., Lebreton, M., Meyniel, F., Bourgeois-Gironde, S. & Palminteri, S. (2017). Behavioural and neural characterization of optimistic reinforcement learning. Nature Human Behaviour , 1(4), 0067

Lelièvre, P. & Neri, P. (2021). A deep-learning framework for human perception of abstract art composition. Journal of vision, 21(5), 9. doi:10.1167/jov.21.5.9

Lenglet, T. , Mirault, J. , Veyrat-Masson, M. , Funkiewiez, A. , Amador, M. , Bruneteau, G. , Le Forestier, N. , Pradat, P. , Salachas, F. , Vacher, Y. , Lacomblez, L. & Lorenceau, J. (2019). Cursive Eye-Writing With Smooth-Pursuit Eye-Movement Is Possible in Subjects With Amyotrophic Lateral Sclerosis. Front Neurosci, 13, 538. doi:10.3389/fnins.2019.00538

Linzen, T., Dupoux, E. & Spector, B. (2016). Quantificational features in distributional word representations. In Proceedings of the Fifth Joint Conference on Lexical and Computational Semantics, pages 1 – 1-11. doi:10.18653/v1/S16-2001

Linzen, T., Dupoux, E. & Goldberg, Y. (2016). Assessing the ability of LSTMs to learn syntax-sensitive dependencies. Transactions of the Association for Computational Linguistics, 4, 521-535

Lo Verde, L., Morrone, M. & Lunghi, C. (2017). Early cross-modal plasticity in adults. Journal of Cognitive Neuroscience, 29(3), 520-529. doi:10.1162/jocn_a_01067

Locke, S., Mamassian, P. & Landy, M. (2018). Sequential Effects in Confidence. Journal of Vision, 18(10), 658

Locke, S., Mamassian, P. & Landy, M. (2020). Performance monitoring for sensorimotor confidence: A visuomotor tracking study. Cognition, 205, 104396. doi:10.1016/j.cognition.2020.104396

Locke, S., Gaffin-Cahn, E. , Hosseinizaveh, N. , Mamassian, P. & Landy, M. (2020). Priors and payoffs in confidence judgments. Attention, Perception, & Psychophysics, 82, 3158–3175. doi:10.3758/s13414-020-02018-x

Locke, S. & Robinson, J. (2021). Affective Bias Through the Lens of Signal Detection Theory. Computational Psychiatry, 5(1), 4. doi:10.5334/cpsy.58

Lopez-Persem, A., Rigoux, L., Bourgeois-Gironde, S., Daunizeau, J. & Pessiglione, M. (2017). Choose, rate or squeeze: Comparison of economic value functions elicited by different behavioral tasks. PLoS computational biology, 13(11), e1005848. doi:10.1371/journal.pcbi.1005848

Ludusan, B., Mazuka, R. & Dupoux, E. (2021). Does infant-directed speech help phonetic learning? A machine learning investigation. Cognitive Science, 45(5), e12946. doi:10.1111/cogs.12946

Ludusan, B. & Dupoux, E. (2016). The role of prosodic boundaries in word discovery: Evidence from a computational model. Journal of the Acoustical Society of America, 140(1), EL1

Ludusan, B. & Dupoux, E. (2016). Automatic syllable segmentation using broad phonetic class information. , Vol. 81: In SLTU-2016 Procedia Computer Science, 101-106.

Ludusan, B., Seidl, A., Dupoux, E. & Cristia, A. (2015). Motif discovery in infant- and adult-directed speech. In Proceedings of CogACLL2015, 93-102. doi:10.18653/v1/W15-2413

Ludusan, B. & Dupoux, E. (2015). A multilingual study on intensity as a cue for marking prosodic boundaries. In ICPhS, e982.

Ludusan, B. & Dupoux, E. (2014). Towards Low Resource Prosodic Boundary Detection. In Proceedings of International Workshop on Spoken Language Technologies for Under-resourced Languages (SLTU'14), 231-237.

Ludusan, B., Gravier, G. & Dupoux, E. (2014). Incorporating Prosodic Boundaries in Unsupervised Term Discovery. , Vol. 7: In Proceedings of Speech Prosody, 939-943.

Ludusan, B., Synnaeve, G. & Dupoux, E. (2015). Prosodic boundary information helps unsupervised word segmentation. In NAACL HLT 2015, 953-963. doi:10.3115/v1/N15-1096

Ludusan, B., Mazuka, R., Bernard, M., Cristia, A. & Dupoux, E. (2017). The Role of Prosody and Speech Register in Word Segmentation: A Computational Modelling Perspective. , Vol. 2: In ACL 2017, 178-183. doi:10.18653/v1/P17-2028

Ludusan, B., Cristia, A., Martin, A., Mazuka, R. & Dupoux, E. (2016). Learnability of prosodic boundaries: Is infant-directed speech easier? Journal of the Acoustical Society of America, 140(2), 1239-1250. doi:10.1121/1.4960576

Ludusan, B., Caranica, A., Cucu, H., Buzo, A., Burileanu, C. & Dupoux, E. (2015 ). Exploring multi-language resources for unsupervised spoken term discovery. In Speech Technology and Human-Computer Dialogue (SpeD), 2015 International Conference on, 1-6.