ChatGPT: Five priorities for research CL van Dis, E. A., Bollen, J., Zuidema, W., van Rooij, R., & Bockting Nature 614 (7947), 224-226, 2023 | 1219 | 2023 |
Quantifying attention flow in transformers S Abnar, W Zuidema arXiv preprint arXiv:2005.00928, 2020 | 716 | 2020 |
Visualisation and 'diagnostic classifiers' reveal how recurrent and recursive neural networks process hierarchical structure D Hupkes, S Veldhoen, W Zuidema Journal of Artificial Intelligence Research 61, 907-926, 2018 | 288 | 2018 |
Simple rules can explain discrimination of putative recursive syntactic structures by a songbird species CAA Van Heijningen, J De Visser, W Zuidema, C Ten Cate Proceedings of the National Academy of Sciences 106 (48), 20538-20543, 2009 | 218 | 2009 |
How the poverty of the stimulus solves the poverty of the stimulus W Zuidema Advances in neural information processing systems, 2003 | 200 | 2003 |
Under the hood: Using diagnostic classifiers to investigate and improve how language models track agreement information M Giulianelli, J Harding, F Mohnert, D Hupkes, W Zuidema Proceedings BlackboxNLP, 2018 | 172 | 2018 |
Children’s grammars grow more abstract with age—Evidence from an automatic procedure for identifying the productive units of language G Borensztajn, W Zuidema, R Bod Topics in Cognitive Science 1 (1), 175-188, 2009 | 153 | 2009 |
Five fundamental constraints on theories of the origins of music B Merker, I Morley, W Zuidema Philosophical Transactions of the Royal Society B: Biological Sciences 370 …, 2015 | 120 | 2015 |
Compositional distributional semantics with long short term memory P Le, W Zuidema arXiv preprint arXiv:1503.02510, 2015 | 120 | 2015 |
The evolution of combinatorial phonology W Zuidema, B De Boer Journal of Phonetics 37 (2), 125-144, 2009 | 114 | 2009 |
Principles of structure building in music, language and animal song M Rohrmeier, W Zuidema, GA Wiggins, C Scharff Philosophical transactions of the Royal Society B: Biological sciences 370 …, 2015 | 91 | 2015 |
The inside-outside recursive neural network model for dependency parsing P Le, W Zuidema Proceedings of the 2014 conference on empirical methods in natural language …, 2014 | 86 | 2014 |
Blackbox meets blackbox: Representational similarity and stability analysis of neural language models and brains S Abnar, L Beinborn, R Choenni, W Zuidema arXiv preprint arXiv:1906.01539, 2019 | 80 | 2019 |
Quantifying the vanishing gradient and long distance dependency problem in recursive neural networks and recursive LSTMs P Le, W Zuidema arXiv preprint arXiv:1603.00423, 2016 | 78 | 2016 |
Experiential, distributional and dependency-based word embeddings have complementary roles in decoding brain activity S Abnar, R Ahmed, M Mijnheer, W Zuidema arXiv preprint arXiv:1711.09285, 2017 | 69 | 2017 |
Multi-agent simulations of the evolution of combinatorial phonology B De Boer, W Zuidema Adaptive Behavior 18 (2), 141-154, 2010 | 61 | 2010 |
Selective advantages of syntactic language--a model study WH Zuidema, P Hogeweg Proceedings of the Annual Meeting of the Cognitive Science Society 22 (22), 2000 | 61 | 2000 |
Transferring inductive biases through knowledge distillation S Abnar, M Dehghani, W Zuidema arXiv preprint arXiv:2006.00555, 2020 | 55 | 2020 |
Diagnostic Classifiers Revealing how Neural Networks Process Hierarchical Structure. S Veldhoen, D Hupkes, WH Zuidema CoCo@ NIPS, 69-77, 2016 | 51 | 2016 |
Modeling in the language sciences B Zuidema, W and Bart de Boer Research methods in linguistics, 422-439, 2014 | 48* | 2014 |