Dieuwke Hupkes
Cited by
Cited by
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...
arXiv preprint arXiv:2206.04615, 2022
Compositionality decomposed: How do neural networks generalise?
D Hupkes, V Dankers, M Mul, E Bruni
Journal of Artificial Intelligence Research 67, 757-795, 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
Masked language modeling and the distributional hypothesis: Order word matters pre-training for little
K Sinha, R Jia, D Hupkes, J Pineau, A Williams, D Kiela
arXiv preprint arXiv:2104.06644, 2021
The emergence of number and syntax units in LSTM language models
Y Lakretz, G Kruszewski, T Desbordes, D Hupkes, S Dehaene, M Baroni
arXiv preprint arXiv:1903.07435, 2019
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
arXiv preprint arXiv:1808.08079, 2018
A taxonomy and review of generalization research in NLP
D Hupkes, M Giulianelli, V Dankers, M Artetxe, Y Elazar, T Pimentel, ...
Nature Machine Intelligence 5 (10), 1161-1174, 2023
Mechanisms for handling nested dependencies in neural-network language models and humans
Y Lakretz, D Hupkes, A Vergallito, M Marelli, M Baroni, S Dehaene
Cognition 213, 104699, 2021
Do language models understand anything? On the ability of LSTMs to understand negative polarity items
J Jumelet, D Hupkes
arXiv preprint arXiv:1808.10627, 2018
The paradox of the compositionality of natural language: A neural machine translation case study
V Dankers, E Bruni, D Hupkes
arXiv preprint arXiv:2108.05885, 2021
Diagnostic Classifiers Revealing how Neural Networks Process Hierarchical Structure.
S Veldhoen, D Hupkes, WH Zuidema
CoCo@ NIPS, 69-77, 2016
Analysing neural language models: Contextual decomposition reveals default reasoning in number and gender assignment
J Jumelet, W Zuidema, D Hupkes
arXiv preprint arXiv:1909.08975, 2019
Co-evolution of language and agents in referential games
G Dagan, D Hupkes, E Bruni
arXiv preprint arXiv:2001.03361, 2020
Location attention for extrapolation to longer sequences
Y Dubois, G Dagan, D Hupkes, E Bruni
arXiv preprint arXiv:1911.03872, 2019
Learning compositionally through attentive guidance
D Hupkes, A Singh, K Korrel, G Kruszewski, E Bruni
arXiv preprint arXiv:1805.09657, 2018
Transcoding compositionally: Using attention to find more generalizable solutions
K Korrel, D Hupkes, V Dankers, E Bruni
arXiv preprint arXiv:1906.01234, 2019
Language models use monotonicity to assess NPI licensing
J Jumelet, M Denić, J Szymanik, D Hupkes, S Steinert-Threlkeld
arXiv preprint arXiv:2105.13818, 2021
How bpe affects memorization in transformers
E Kharitonov, M Baroni, D Hupkes
arXiv preprint arXiv:2110.02782, 2021
Generalising to German plural noun classes, from the perspective of a recurrent neural network
V Dankers, A Langedijk, K McCurdy, A Williams, D Hupkes
Proceedings of the 25th Conference on Computational Natural Language …, 2021
Sparse interventions in language models with differentiable masking
N De Cao, L Schmid, D Hupkes, I Titov
arXiv preprint arXiv:2112.06837, 2021
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