Marten van Schijndel

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	All	Since 2016
Citations	371	334
h-index	13	12
i10-index	14	13

140

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2013201420152016201720182019202020216 12 19 37 42 55 57 121 18

Co-authors

Tal LinzenNew York UniversityVerified email at jhu.edu
Cory ShainOhio State UniversityVerified email at osu.edu
Edward (Ted) GibsonProfessor of Cognitive Science, MITVerified email at mit.edu
Richard FutrellAssistant Professor, UC Irvine Language ScienceVerified email at uci.edu
Evelina (Ev) FedorenkoMIT, Associate ProfessorVerified email at mit.edu
Forrest DavisPh.D candidate, Linguistics, Cornell UniversityVerified email at cornell.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
Aaron MuellerPh.D. Student, Johns Hopkins UniversityVerified email at jhu.edu
Idan Asher BlankAssistant Professor, UCLAVerified email at psych.ucla.edu
Michael WhiteProfessor of Linguistics, The Ohio State UniversityVerified 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
Micha ElsnerAssistant Professor of Linguistics, The Ohio State UniversityVerified email at ling.ohio-state.edu
Lifeng JinTencent AmericaVerified email at osu.edu
David L. KingGraduate Researcher, Ohio State UniversityVerified email at osu.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


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
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	34	2013
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	32	2016
Modeling garden path effects without explicit hierarchical syntax. M Van Schijndel, T Linzen CogSci, 2018	29	2018
Quantity doesn't buy quality syntax with neural language models M Van Schijndel, A Mueller, T Linzen arXiv preprint arXiv:1909.00111, 2019	28	2019
Hierarchic syntax improves reading time prediction M Van Schijndel, W Schuler Proceedings of the 2015 Conference of the North American Chapter of the …, 2015	27	2015
Accurate Unbounded Dependency Recovery using Generalized Categorial Grammars. L Nguyen, M Van Schijndel, W Schuler Proceedings of COLING, 2125-2140, 2012	26	2012
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	25	2020
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	24	2016
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	23	2016
A Neural Model of Adaptation in Reading M van Schijndel, T Linzen EMNLP 2018, 2018	20	2018
An Analysis of Frequency- and Memory-Based Processing Costs. M Van Schijndel, W Schuler Proceedings of NAACL-HLT, 95-105, 2013	20	2013
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
Using priming to uncover the organization of syntactic representations in neural language models G Prasad, M Van Schijndel, T Linzen arXiv preprint arXiv:1909.10579, 2019	13	2019
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	11	2013
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	7	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
Recurrent neural network language models always learn English-like relative clause attachment F Davis, M Van Schijndel arXiv preprint arXiv:2005.00165, 2020	5	2020
Approximations of Predictive Entropy Correlate with Reading Times. M Van Schijndel, W Schuler CogSci, 2017	5	2017
Can Entropy Explain Successor Surprisal Effects in Reading? M Van Schijndel, T Linzen arXiv preprint arXiv:1810.11481, 2018	3	2018

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