Dieuwke Hupkes
According to our database1,
Dieuwke Hupkes
authored at least 47 papers
between 2016 and 2023.
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Bibliography
2023
Nat. Mac. Intell., October, 2023
CoRR, 2023
Separating form and meaning: Using self-consistency to quantify task understanding across multiple senses.
CoRR, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Memorisation Cartography: Mapping out the Memorisation-Generalisation Continuum in Neural Machine Translation.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Mind the instructions: a holistic evaluation of consistency and interactions in prompt-based learning.
Proceedings of the 27th Conference on Computational Natural Language Learning, 2023
The Validity of Evaluation Results: Assessing Concurrence Across Compositionality Benchmarks.
Proceedings of the 27th Conference on Computational Natural Language Learning, 2023
2022
Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, 2022
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022
Proceedings of the 29th International Conference on Computational Linguistics, 2022
Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2022
The Paradox of the Compositionality of Natural Language: A Neural Machine Translation Case Study.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022
2021
Causal Transformers Perform Below Chance on Recursive Nested Constructions, Unlike Humans.
CoRR, 2021
Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021
Generalising to German Plural Noun Classes, from the Perspective of a Recurrent Neural Network.
Proceedings of the 25th Conference on Computational Natural Language Learning, 2021
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021
Proceedings of Deep Learning Inside Out: The 2nd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures, 2021
2020
J. Artif. Intell. Res., 2020
Exploring Processing of Nested Dependencies in Neural-Network Language Models and Humans.
CoRR, 2020
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020
Internal and External Pressures on Language Emergence: Least Effort, Object Constancy and Frequency.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020
2019
CoRR, 2019
Proceedings of the 4th Workshop on Representation Learning for NLP, 2019
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019
The Fast and the Flexible: Training Neural Networks to Learn to Follow Instructions from Small Data.
Proceedings of the 13th International Conference on Computational Semantics, 2019
Analysing Neural Language Models: Contextual Decomposition Reveals Default Reasoning in Number and Gender Assignment.
Proceedings of the 23rd Conference on Computational Natural Language Learning, 2019
Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, 2019
Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, 2019
2018
Visualisation and 'Diagnostic Classifiers' Reveal How Recurrent and Recursive Neural Networks Process Hierarchical Structure.
J. Artif. Intell. Res., 2018
Visualisation and 'Diagnostic Classifiers' Reveal how Recurrent and Recursive Neural Networks Process Hierarchical Structure (Extended Abstract).
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018
Do Language Models Understand Anything? On the Ability of LSTMs to Understand Negative Polarity Items.
Proceedings of the Workshop: Analyzing and Interpreting Neural Networks for NLP, 2018
Analysing the potential of seq-to-seq models for incremental interpretation in task-oriented dialogue.
Proceedings of the Workshop: Analyzing and Interpreting Neural Networks for NLP, 2018
Under the Hood: Using Diagnostic Classifiers to Investigate and Improve how Language Models Track Agreement Information.
Proceedings of the Workshop: Analyzing and Interpreting Neural Networks for NLP, 2018
2016
Proceedings of the Workshop on Cognitive Computation: Integrating neural and symbolic approaches 2016 co-located with the 30th Annual Conference on Neural Information Processing Systems (NIPS 2016), 2016
Proceedings of the Tenth International Conference on Language Resources and Evaluation LREC 2016, 2016