Marten van Schijndel

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Tal LinzenNew York UniversityVerified email at nyu.edu
Cory ShainMassachusetts Institute of TechnologyVerified email at mit.edu
Edward (Ted) GibsonProfessor of Cognitive Science, MITVerified email at mit.edu
Forrest DavisPh.D candidate, Linguistics, Cornell UniversityVerified email at cornell.edu
Richard FutrellAssistant Professor, UC Irvine Language ScienceVerified email at uci.edu
Evelina (Ev) FedorenkoMIT, Associate ProfessorVerified email at mit.edu
Idan Asher BlankAssistant Professor, UCLAVerified email at psych.ucla.edu
Aaron MuellerPh.D. Student, Johns Hopkins UniversityVerified email at jhu.edu
Vera DembergSaarland University, Saarland Informatics CampusVerified email at coli.uni-saarland.de
Alessandra ZarconeFraunhofer IISVerified email at iis.fraunhofer.de
J. VogelsVerified email at rug.nl
Michael WhiteProfessor of Linguistics, The Ohio State University / Research Scientist, FacebookVerified email at ling.osu.edu
Rajakrishnan RajkumarDept of Humanities and Social Sciences, IISER BhopalVerified email at iiserb.ac.in
Grusha PrasadJohns Hopkins UniversityVerified email at jhu.edu
Lifeng JinTencent AmericaVerified email at osu.edu
David L. KingGraduate Researcher, Ohio State UniversityVerified email at osu.edu
William TimkeyCornell UniversityVerified email at cornell.edu
Micha ElsnerAssistant Professor of Linguistics, The Ohio State UniversityVerified email at ling.ohio-state.edu
Kathleen C. FraserNational Research CouncilVerified email at nrc-cnrc.gc.ca
Debasmita BhattacharyaMaster's student, Computer Science, Cornell University College of EngineeringVerified email at cornell.edu

Marten van Schijndel

Cornell University

Verified email at cornell.edu - Homepage

Computational Linguistics Psycholinguistics Syntax Semantics


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A model of language processing as hierarchic sequential prediction M van Schijndel, A Exley, W Schuler Topics in Cognitive Science 5 (3), 522-540, 2013	49	2013
fMRI reveals language-specific predictive coding during naturalistic sentence comprehension C Shain, IA Blank, M van Schijndel, W Schuler, E Fedorenko Neuropsychologia 138, 107307, 2020	48	2020
A Neural Model of Adaptation in Reading M van Schijndel, T Linzen Proceedings of EMNLP 2018, 2018	42	2018
Quantity doesn't buy quality syntax with neural language models M Van Schijndel, A Mueller, T Linzen Proceedings of EMNLP 2019, 2019	39	2019
Modeling garden path effects without explicit hierarchical syntax. M Van Schijndel, T Linzen Proceedings of CogSci 2018, 2018	37	2018
Salience and attention in surprisal-based accounts of language processing A Zarcone, M Van Schijndel, J Vogels, V Demberg Frontiers in psychology 7, 844, 2016	37	2016
Hierarchic syntax improves reading time prediction M Van Schijndel, W Schuler Proceedings of the 2015 Conference of the North American Chapter of the …, 2015	35	2015
Accurate Unbounded Dependency Recovery using Generalized Categorial Grammars. L Nguyen, M Van Schijndel, W Schuler Proceedings of COLING, 2125-2140, 2012	32	2012
Memory access during incremental sentence processing causes reading time latency C Shain, M Van Schijndel, R Futrell, E Gibson, W Schuler Proceedings of the workshop on computational linguistics for linguistic …, 2016	30	2016
Investigating locality effects and surprisal in written English syntactic choice phenomena R Rajkumar, M Van Schijndel, M White, W Schuler Cognition 155, 204-232, 2016	29	2016
An Analysis of Frequency- and Memory-Based Processing Costs. M Van Schijndel, W Schuler Proceedings of NAACL-HLT, 95-105, 2013	26	2013
Using priming to uncover the organization of syntactic representations in neural language models G Prasad, M Van Schijndel, T Linzen Proceedings of the 23rd Conference on Computational Natural Language Learning, 2019	22	2019
Frequency effects in the processing of unbounded dependencies M van Schijndel, W Schuler, PW Culicover Annual Meeting of the Cognitive Science Society (CogSci), 2014	14	2014
An analysis of memory-based processing costs using incremental deep syntactic dependency parsing M Van Schijndel, L Nguyen, W Schuler Workshop on Cognitive Modeling and Computational Linguistics (CMCL), 2013	12	2013
Recurrent neural network language models always learn English-like relative clause attachment F Davis, M Van Schijndel Proceedings of ACL 2020, 2020	11	2020
Evidence of syntactic working memory usage in MEG data M van Schijndel, B Murphy, W Schuler Workshop on Cognitive Modeling and Computational Linguistics (CMCL), 2015	8	2015
Addressing surprisal deficiencies in reading time models. M Van Schijndel, W Schuler CL4LC@ COLING 2016, 32-37, 2016	6	2016
Connectionist-inspired incremental PCFG parsing M van Schijndel, A Exley, W Schuler Workshop on Cognitive Modeling and Computational Linguistics (CMCL), 51-60, 2012	6	2012
Single‐Stage Prediction Models Do Not Explain the Magnitude of Syntactic Disambiguation Difficulty M Van Schijndel, T Linzen Cognitive Science 45 (6), e12988, 2021	5	2021
Discourse structure interacts with reference but not syntax in neural language models F Davis, M Van Schijndel arXiv preprint arXiv:2010.04887, 2020	5	2020

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