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Willem H. Zuidema
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- affiliation: University of Amsterdam, The Netherlands
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2020 – today
- 2024
- [j14]Oskar van der Wal
, Dominik Bachmann, Alina Leidinger
Undesirable Biases in NLP: Addressing Challenges of Measurement. J. Artif. Intell. Res. 79: 1-40 (2024) - [j13]Dominik Bachmann, Oskar van der Wal, Edita Chvojka
fl-IRT-ing with Psychometrics to Improve NLP Bias Measurement. Minds Mach. 34(4): 37 (2024) - [c41]Jaap Jumelet, Willem H. Zuidema, Arabella Sinclair:
Do Language Models Exhibit Human-like Structural Priming Effects? ACL (Findings) 2024: 14727-14742 - [c40]Anna Langedijk, Hosein Mohebbi, Gabriele Sarti, Willem H. Zuidema, Jaap Jumelet:
DecoderLens: Layerwise Interpretation of Encoder-Decoder Transformers. NAACL-HLT (Findings) 2024: 4764-4780 - [i28]Jaap Jumelet, Willem H. Zuidema, Arabella Sinclair:
Do Language Models Exhibit Human-like Structural Priming Effects? CoRR abs/2406.04847 (2024) - [i27]Charlotte Pouw, Marianne de Heer Kloots, Afra Alishahi, Willem H. Zuidema:
Perception of Phonological Assimilation by Neural Speech Recognition Models. CoRR abs/2406.15265 (2024) - [i26]Jaap Jumelet, Lisa Bylinina, Willem H. Zuidema, Jakub Szymanik:
Black Big Boxes: Do Language Models Hide a Theory of Adjective Order? CoRR abs/2407.02136 (2024) - [i25]Marianne de Heer Kloots, Willem H. Zuidema:
Human-like Linguistic Biases in Neural Speech Models: Phonetic Categorization and Phonotactic Constraints in Wav2Vec2.0. CoRR abs/2407.03005 (2024) - [i24]Hosein Mohebbi, Grzegorz Chrupala, Willem H. Zuidema, Afra Alishahi, Ivan Titov:
Disentangling Textual and Acoustic Features of Neural Speech Representations. CoRR abs/2410.03037 (2024) - [i23]Angela van Sprang, Erman Acar, Willem H. Zuidema:
Enforcing Interpretability in Time Series Transformers: A Concept Bottleneck Framework. CoRR abs/2410.06070 (2024) - 2023
- [c39]Jaap Jumelet, Willem H. Zuidema:
Feature Interactions Reveal Linguistic Structure in Language Models. ACL (Findings) 2023: 8697-8712 - [c38]Abhijith Chintam, Rahel Beloch, Willem H. Zuidema, Michael Hanna
Identifying and Adapting Transformer-Components Responsible for Gender Bias in an English Language Model. BlackboxNLP@EMNLP 2023: 379-394 - [c37]Hosein Mohebbi, Willem H. Zuidema, Grzegorz Chrupala, Afra Alishahi:
Quantifying Context Mixing in Transformers. EACL 2023: 3370-3392 - [c36]Jaap Jumelet, Willem H. Zuidema:
Transparency at the Source: Evaluating and Interpreting Language Models With Access to the True Distribution. EMNLP (Findings) 2023: 4354-4369 - [c35]Hosein Mohebbi
Homophone Disambiguation Reveals Patterns of Context Mixing in Speech Transformers. EMNLP 2023: 8249-8260 - [c34]Marcel A. Vélez Vásquez, Mariëlle Baelemans, Jonathan Driedger, Willem H. Zuidema, John Ashley Burgoyne
Quantifying the Ease of Playing Song Chords on the Guitar. ISMIR 2023: 725-732 - [i22]Hosein Mohebbi, Willem H. Zuidema, Grzegorz Chrupala, Afra Alishahi:
Quantifying Context Mixing in Transformers. CoRR abs/2301.12971 (2023) - [i21]Jaap Jumelet, Willem H. Zuidema:
Feature Interactions Reveal Linguistic Structure in Language Models. CoRR abs/2306.12181 (2023) - [i20]Anna Langedijk, Hosein Mohebbi, Gabriele Sarti
DecoderLens: Layerwise Interpretation of Encoder-Decoder Transformers. CoRR abs/2310.03686 (2023) - [i19]Hosein Mohebbi, Grzegorz Chrupala, Willem H. Zuidema, Afra Alishahi:
Homophone Disambiguation Reveals Patterns of Context Mixing in Speech Transformers. CoRR abs/2310.09925 (2023) - [i18]Abhijith Chintam, Rahel Beloch, Willem H. Zuidema, Michael Hanna, Oskar van der Wal:
Identifying and Adapting Transformer-Components Responsible for Gender Bias in an English Language Model. CoRR abs/2310.12611 (2023) - [i17]Jaap Jumelet, Willem H. Zuidema:
Transparency at the Source: Evaluating and Interpreting Language Models With Access to the True Distribution. CoRR abs/2310.14840 (2023) - 2022
- [j12]Arabella J. Sinclair, Jaap Jumelet, Willem H. Zuidema, Raquel Fernández:
Structural Persistence in Language Models: Priming as a Window into Abstract Language Representations. Trans. Assoc. Comput. Linguistics 10: 1031-1050 (2022) - [i16]Oskar van der Wal, Jaap Jumelet, Katrin Schulz, Willem H. Zuidema:
The Birth of Bias: A case study on the evolution of gender bias in an English language model. CoRR abs/2207.10245 (2022) - [i15]Oskar van der Wal, Dominik Bachmann, Alina Leidinger, Leendert van Maanen, Willem H. Zuidema, Katrin Schulz:
Undesirable biases in NLP: Averting a crisis of measurement. CoRR abs/2211.13709 (2022) - 2021
- [c33]Bas Cornelissen, Willem H. Zuidema, John Ashley Burgoyne:
Cosine Contours: a Multipurpose Representation for Melodies. ISMIR 2021: 135-142 - [i14]Arabella Sinclair, Jaap Jumelet, Willem H. Zuidema, Raquel Fernández:
Syntactic Persistence in Language Models: Priming as a Window into Abstract Language Representations. CoRR abs/2109.14989 (2021) - 2020
- [j11]Peter Dekker
Word prediction in computational historical linguistics. J. Lang. Model. 8(2) (2020) - [j10]Carel ten Cate, Judit Gervain
Editors' Review and Introduction: Learning Grammatical Structures: Developmental, Cross-Species, and Computational Approaches. Top. Cogn. Sci. 12(3): 804-814 (2020) - [j9]Julia Uddén, Maurício de Jesus Dias Martins
Hierarchical Structure in Sequence Processing: How to Measure It and Determine Its Neural Implementation. Top. Cogn. Sci. 12(3): 910-924 (2020) - [j8]Willem H. Zuidema, Robert M. French, Raquel G. Alhama, Kevin Ellis, Timothy J. O'Donnell, Tim Sainburg, Timothy Gentner:
Five Ways in Which Computational Modeling Can Help Advance Cognitive Science: Lessons From Artificial Grammar Learning. Top. Cogn. Sci. 12(3): 925-941 (2020) - [c32]Samira Abnar, Willem H. Zuidema:
Quantifying Attention Flow in Transformers. ACL 2020: 4190-4197 - [c31]Phong Le, Willem H. Zuidema:
DoLFIn: Distributions over Latent Features for Interpretability. COLING 2020: 1468-1474 - [c30]Bas Cornelissen
Studying Large Plainchant Corpora Using chant21. DLfM 2020: 40-44 - [c29]Bas Cornelissen, Willem H. Zuidema, John Ashley Burgoyne:
Mode classification and natural units in plainchant. ISMIR 2020: 869-875 - [i13]Samira Abnar, Willem H. Zuidema:
Quantifying Attention Flow in Transformers. CoRR abs/2005.00928 (2020) - [i12]Samira Abnar, Mostafa Dehghani, Willem H. Zuidema:
Transferring Inductive Biases through Knowledge Distillation. CoRR abs/2006.00555 (2020) - [i11]Phong Le, Willem H. Zuidema:
DoLFIn: Distributions over Latent Features for Interpretability. CoRR abs/2011.05295 (2020)
2010 – 2019
- 2019
- [c28]Samira Abnar, Lisa Beinborn, Rochelle Choenni, Willem H. Zuidema:
Blackbox Meets Blackbox: Representational Similarity & Stability Analysis of Neural Language Models and Brains. BlackboxNLP@ACL 2019: 191-203 - [c27]Jaap Jumelet, Willem H. Zuidema, Dieuwke Hupkes:
Analysing Neural Language Models: Contextual Decomposition Reveals Default Reasoning in Number and Gender Assignment. CoNLL 2019: 1-11 - [i10]Willem H. Zuidema, Dieuwke Hupkes, Geraint A. Wiggins, Constance Scharff, Martin Rohrmeier:
Formal models of Structure Building in Music, Language and Animal Songs. CoRR abs/1901.05180 (2019) - [i9]Mathijs Mul, Willem H. Zuidema:
Siamese recurrent networks learn first-order logic reasoning and exhibit zero-shot compositional generalization. CoRR abs/1906.00180 (2019) - [i8]Samira Abnar, Lisa Beinborn, Rochelle Choenni, Willem H. Zuidema:
Blackbox meets blackbox: Representational Similarity and Stability Analysis of Neural Language Models and Brains. CoRR abs/1906.01539 (2019) - [i7]Jaap Jumelet, Willem H. Zuidema, Dieuwke Hupkes:
Analysing Neural Language Models: Contextual Decomposition Reveals Default Reasoning in Number and Gender Assignment. CoRR abs/1909.08975 (2019) - 2018
- [j7]Dieuwke Hupkes, Sara Veldhoen
Visualisation and 'Diagnostic Classifiers' Reveal How Recurrent and Recursive Neural Networks Process Hierarchical Structure. J. Artif. Intell. Res. 61: 907-926 (2018) - [j6]Raquel G. Alhama, Willem H. Zuidema:
Pre-Wiring and Pre-Training: What Does a Neural Network Need to Learn Truly General Identity Rules? J. Artif. Intell. Res. 61: 927-946 (2018) - [c26]Samira Abnar, Rasyan Ahmed, Max Mijnheer, Willem H. Zuidema:
Experiential, Distributional and Dependency-based Word Embeddings have Complementary Roles in Decoding Brain Activity. CMCL 2018: 57-66 - [c25]Mario Giulianelli, Jack Harding, Florian Mohnert, Dieuwke Hupkes, Willem H. Zuidema:
Under the Hood: Using Diagnostic Classifiers to Investigate and Improve how Language Models Track Agreement Information. BlackboxNLP@EMNLP 2018: 240-248 - [c24]Dieuwke Hupkes, Willem H. Zuidema:
Visualisation and 'Diagnostic Classifiers' Reveal how Recurrent and Recursive Neural Networks Process Hierarchical Structure (Extended Abstract). IJCAI 2018: 5617-5621 - [i6]Mario Giulianelli, Jack Harding, Florian Mohnert, Dieuwke Hupkes, Willem H. Zuidema:
Under the Hood: Using Diagnostic Classifiers to Investigate and Improve how Language Models Track Agreement Information. CoRR abs/1808.08079 (2018) - 2017
- [c23]Raquel G. Alhama, Willem H. Zuidema:
Segmentation as Retention and Recognition: the R&R model. CogSci 2017 - [i5]Samira Abnar, Rasyan Ahmed, Max Mijnheer, Willem H. Zuidema:
Experiential, Distributional and Dependency-based Word Embeddings have Complementary Roles in Decoding Brain Activity. CoRR abs/1711.09285 (2017) - [i4]Dieuwke Hupkes, Sara Veldhoen, Willem H. Zuidema:
Visualisation and 'diagnostic classifiers' reveal how recurrent and recursive neural networks process hierarchical structure. CoRR abs/1711.10203 (2017) - 2016
- [c22]Raquel G. Alhama, Willem H. Zuidema:
Pre-Wiring and Pre-Training: What Does a Neural Network Need to Learn Truly General Identity Rules? CoCo@NIPS 2016 - [c21]Sara Veldhoen, Dieuwke Hupkes, Willem H. Zuidema:
Diagnostic Classifiers Revealing how Neural Networks Process Hierarchical Structure. CoCo@NIPS 2016 - [c20]Phong Le, Willem H. Zuidema
Quantifying the Vanishing Gradient and Long Distance Dependency Problem in Recursive Neural Networks and Recursive LSTMs. Rep4NLP@ACL 2016: 87-93 - [i3]Phong Le, Willem H. Zuidema:
Quantifying the vanishing gradient and long distance dependency problem in recursive neural networks and recursive LSTMs. CoRR abs/1603.00423 (2016) - 2015
- [c19]Phong Le, Willem H. Zuidema:
The Forest Convolutional Network: Compositional Distributional Semantics with a Neural Chart and without Binarization. EMNLP 2015: 1155-1164 - [c18]Phong Le, Willem H. Zuidema:
Unsupervised Dependency Parsing: Let's Use Supervised Parsers. HLT-NAACL 2015: 651-661 - [c17]Phong Le, Willem H. Zuidema
Compositional Distributional Semantics with Long Short Term Memory. *SEM@NAACL-HLT 2015: 10-19 - [i2]Phong Le, Willem H. Zuidema:
Compositional Distributional Semantics with Long Short Term Memory. CoRR abs/1503.02510 (2015) - [i1]Phong Le, Willem H. Zuidema:
Unsupervised Dependency Parsing: Let's Use Supervised Parsers. CoRR abs/1504.04666 (2015) - 2014
- [c16]Phong Le, Willem H. Zuidema
The Inside-Outside Recursive Neural Network model for Dependency Parsing. EMNLP 2014: 729-739 - 2013
- [c15]Phong Le, Willem H. Zuidema, Remko Scha:
Learning from errors: Using vector-based compositional semantics for parse reranking. CVSM@ACL 2013: 11-19 - [c14]Willem H. Zuidema:
Context-freeness Revisited. CogSci 2013 - 2012
- [c13]Phong Le, Willem H. Zuidema:
Learning Compositional Semantics for Open Domain Semantic Parsing. COLING 2012: 1535-1552 - 2011
- [c12]Gideon Borensztajn, Willem H. Zuidema:
Episodic grammar: a computational model of the interaction between episodic and semantic memory in language processing. CogSci 2011 - [c11]Federico Sangati, Willem H. Zuidema:
Accurate Parsing with Compact Tree-Substitution Grammars: Double-DOP. EMNLP 2011: 84-95 - 2010
- [j5]Willem H. Zuidema
What Are the Unique Design Features of Language? Formal Tools for Comparative Claims. Adapt. Behav. 18(1): 48-65 (2010) - [j4]Bart de Boer, Willem H. Zuidema
Multi-Agent Simulations of the Evolution of Combinatorial Phonology. Adapt. Behav. 18(2): 141-154 (2010) - [c10]Federico Sangati, Willem H. Zuidema, Rens Bod:
Efficiently Extract Recurring Tree Fragments from Large Treebanks. LREC 2010
2000 – 2009
- 2009
- [j3]Willem H. Zuidema
The evolution of combinatorial phonology. J. Phonetics 37(2): 125-144 (2009) - [j2]Gideon Borensztajn, Willem H. Zuidema
Children's Grammars Grow More Abstract with Age - Evidence from an Automatic Procedure for Identifying the Productive Units of Language. Top. Cogn. Sci. 1(1): 175-188 (2009) - [c9]Federico Sangati, Willem H. Zuidema:
Unsupervised Methods for Head Assignments. EACL 2009: 701-709 - [c8]Federico Sangati, Willem H. Zuidema, Rens Bod:
A generative re-ranking model for dependency parsing. IWPT 2009: 238-241 - 2007
- [c7]Willem H. Zuidema:
Parsimonious Data-Oriented Parsing. EMNLP-CoNLL 2007: 551-560 - 2006
- [c6]Willem H. Zuidema:
What are the Productive Units of Natural Language Grammar? A DOP Approach to the Automatic Identification of Constructions. CoNLL 2006: 29-36 - [c5]Willem H. Zuidema:
Theoretical Evaluation of Estimation Methods for Data-Oriented Parsing. EACL 2006 - 2005
- [c4]Bart de Boer, Willem H. Zuidema:
Multi-Agent Simulations of the Evolution of Combinatorial Phonology. BNAIC 2005: 66-73 - 2003
- [j1]Willem H. Zuidema
Evolution of an Optimal Lexicon under Constraints from Embodiment. Artif. Life 9(4): 387-402 (2003) - [c3]Willem H. Zuidema:
Optimal Communication in a Noisy and Heterogeneous Environment. ECAL 2003: 553-563 - 2002
- [c2]Willem H. Zuidema:
How the Poverty of the Stimulus Solves the Poverty of the Stimulus. NIPS 2002: 43-50 - 2001
- [c1]Willem H. Zuidema:
Emergent Syntax: The Unremitting Value of Computational Modeling for Understanding the Origins of Complex Language. ECAL 2001: 641-644
Coauthor Index
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last updated on 2024-12-10 20:49 CET by the dblp team
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