Raquel G. Alhama
Raquel G. Alhama
Cognitive Science and Artificial Intelligence Department, Tilburg University
Verified email at - Homepage
Cited by
Cited by
Pre-Wiring and Pre-Training: What does a neural network need to learn truly general identity rules?
RG Alhama, W Zuidema
Journal of Artificial Intelligence Research 61, 927-946, 2018
A review of computational models of basic rule learning: The neural-symbolic debate and beyond
RG Alhama, W Zuidema
Psychonomic bulletin & review 26, 1174-1194, 2019
Neural discontinuous constituency parsing
M Stanojevic, RG Alhama
2017 Conference on Empirical Methods in Natural Language Processing, 1666-1676, 2017
Five ways in which computational modeling can help advance cognitive science: Lessons from artificial grammar learning
W Zuidema, RM French, RG Alhama, K Ellis, TJ O'Donnell, T Sainburg, ...
Topics in cognitive science 12 (3), 925-941, 2020
How should we evaluate models of segmentation in artificial language learning?
RG Alhama, R Scha, W Zudema
University of Groningen, 2015
When the “Tabula” is anything but “Rasa:” What determines performance in the auditory statistical learning task?
A Elazar, RG Alhama, L Bogaerts, N Siegelman, C Baus, R Frost
Cognitive Science 46 (2), e13102, 2022
The role of information in visual word recognition: A perceptually-constrained connectionist account
RG Alhama, N Siegelman, R Frost, BC Armstrong
The 41st annual meeting of the cognitive science society (cogsci 2019), 83-89, 2019
Segmentation as Retention and Recognition: the R&R model
RG Alhama, W Zuidema
Proceedings of the 39th Annual Conference of the Cognitive Science Society., 2017
Evaluating word embeddings for language acquisition
RG Alhama, CF Rowland, E Kidd
(Online) Workshop on Cognitive Modeling and Computational Linguistics (CMCL …, 2020
Computational modelling of artificial language learning: Retention, recognition & recurrence
RG Alhama
University of Amsterdam, 2017
Generalization in Artificial Language Learning: Modelling the Propensity to Generalize
RG Alhama, W Zuidema
Proceedings of the 7th Workshop on Cognitive Aspects of Computational …, 2016
Los avances tecnológicos y la ciencia del lenguaje
M Martí, RG Alhama, M Recasens
Universidad de Santiago de Compostela, 2012
Rule learning in humans and animals
RG Alhama, R Scha, W Zuidema
Proceedings of the international conference on the evolution of language …, 2014
Word Segmentation as Unsupervised Constituency Parsing
RG Alhama
Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022
Retrodiction as Delayed Recurrence: the Case of Adjectives in Italian and English
RG Alhama, F Zermiani, A Khaliq
Proceedings of the The 19th Annual Workshop of the Australasian Language …, 2021
How much context is helpful for noun and verb acquisition?
RG Alhama, C Rowland, E Kidd
International Conference on Cognitive Modelling, 2021
'Long nose’and ‘naso lungo’: Establishing the need for retrodiction in computational models of word learning
F Zermiani, A Khaliq, RG Alhama
Many Paths to Language, 2020
Distributional semantic models for vocabulary acquisition
RG Alhama, C Rowland, E Kidd
the 26th Architectures and Mechanisms for Language Processing Conference …, 2020
Five ways in which computational models can help advancing Artificial Grammar Learning research
WH Zuidema, R French, RG Alhama, K Ellis, T O'Donell, T Sainburgh, ...
Topics in Cognitive Science, 2019
Predictive generation of syntax during sentence reading
J Martorell, RG Alhama, N Molinaro, S Mancini
the XIV International Symposium of Psycholinguistics, 2019
The system can't perform the operation now. Try again later.
Articles 1–20