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ORCIDMarten van Schijndel
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- affiliation: Cornell University, Ithaka, NY, USA
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2020 – today
- 2024
[c27]Jacob Matthews, John Starr, Marten van Schijndel:
Semantics or spelling? Probing contextual word embeddings with orthographic noise. ACL (Findings) 2024: 4495-4504- [i14]Sidharth Ranjan, Marten van Schijndel:
Does Dependency Locality Predict Non-canonical Word Order in Hindi? CoRR abs/2405.07730 (2024) - [i13]Jacob Matthews, John Starr, Marten van Schijndel:
Semantics or spelling? Probing contextual word embeddings with orthographic noise. CoRR abs/2408.04162 (2024) - [i12]Debasmita Bhattacharya, Marten van Schijndel:
Code-switching in text and speech reveals information-theoretic audience design. CoRR abs/2408.04596 (2024) - 2023
- [c26]Fangcong Yin, Marten van Schijndel:
Linguistic Compression in Single-Sentence Human-Written Summaries. EMNLP (Findings) 2023: 7922-7935 - 2022
- [c25]Sidharth Ranjan, Marten van Schijndel
, Sumeet Agarwal, Rajakrishnan Rajkumar:
Discourse Context Predictability Effects in Hindi Word Order. EMNLP 2022: 10390-10406 - [c24]Sidharth Ranjan, Marten van Schijndel, Sumeet Agarwal, Rajakrishnan Rajkumar:
Dual Mechanism Priming Effects in Hindi Word Order. AACL/IJCNLP (1) 2022: 936-953 - [i11]Sidharth Ranjan, Marten van Schijndel, Sumeet Agarwal, Rajakrishnan Rajkumar:
Dual Mechanism Priming Effects in Hindi Word Order. CoRR abs/2210.13938 (2022) - [i10]Sidharth Ranjan, Marten van Schijndel, Sumeet Agarwal, Rajakrishnan Rajkumar:
Discourse Context Predictability Effects in Hindi Word Order. CoRR abs/2210.13940 (2022) - 2021
- [j2]Marten van Schijndel, Tal Linzen:
Single-Stage Prediction Models Do Not Explain the Magnitude of Syntactic Disambiguation Difficulty. Cogn. Sci. 45(6) (2021) - [c23]Forrest Davis, Marten van Schijndel:
Uncovering Constraint-Based Behavior in Neural Models via Targeted Fine-Tuning. ACL/IJCNLP (1) 2021: 1159-1171 - [c22]Matt Wilber, William Timkey, Marten van Schijndel:
To Point or Not to Point: Understanding How Abstractive Summarizers Paraphrase Text. ACL/IJCNLP (Findings) 2021: 3362-3376 - [c21]William Timkey, Marten van Schijndel:
All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality. EMNLP (1) 2021: 4527-4546 - [i9]Forrest Davis, Marten van Schijndel:
Uncovering Constraint-Based Behavior in Neural Models via Targeted Fine-Tuning. CoRR abs/2106.01207 (2021) - [i8]Matt Wilber, William Timkey, Marten van Schijndel:
To Point or Not to Point: Understanding How Abstractive Summarizers Paraphrase Text. CoRR abs/2106.01581 (2021) - [i7]William Timkey, Marten van Schijndel:
All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality. CoRR abs/2109.04404 (2021) - 2020
- [c20]Forrest Davis, Marten van Schijndel:
Recurrent Neural Network Language Models Always Learn English-Like Relative Clause Attachment. ACL 2020: 1979-1990 - [c19]Forrest Davis, Marten van Schijndel:
Interaction with Context During Recurrent Neural Network Sentence Processing. CogSci 2020 - [c18]Forrest Davis, Marten van Schijndel:
Discourse structure interacts with reference but not syntax in neural language models. CoNLL 2020: 396-407 - [c17]Debasmita Bhattacharya, Marten van Schijndel:
Filler-gaps that neural networks fail to generalize. CoNLL 2020: 486-495 - [i6]Forrest Davis, Marten van Schijndel:
Recurrent Neural Network Language Models Always Learn English-Like Relative Clause Attachment. CoRR abs/2005.00165 (2020) - [i5]Forrest Davis, Marten van Schijndel:
Discourse structure interacts with reference but not syntax in neural language models. CoRR abs/2010.04887 (2020)
2010 – 2019
- 2019
- [c16]Grusha Prasad, Marten van Schijndel, Tal Linzen:
Using Priming to Uncover the Organization of Syntactic Representations in Neural Language Models. CoNLL 2019: 66-76 - [c15]Marten van Schijndel, Aaron Mueller, Tal Linzen:
Quantity doesn't buy quality syntax with neural language models. EMNLP/IJCNLP (1) 2019: 5830-5836 - [i4]Marten van Schijndel, Aaron Mueller, Tal Linzen:
Quantity doesn't buy quality syntax with neural language models. CoRR abs/1909.00111 (2019) - [i3]Grusha Prasad, Marten van Schijndel, Tal Linzen:
Using Priming to Uncover the Organization of Syntactic Representations in Neural Language Models. CoRR abs/1909.10579 (2019) - 2018
- [c14]Marten van Schijndel, Tal Linzen:
Modeling garden path effects without explicit hierarchical syntax. CogSci 2018 - [c13]Marten van Schijndel, Tal Linzen:
A Neural Model of Adaptation in Reading. EMNLP 2018: 4704-4710 - [e3]Asad B. Sayeed, Cassandra Jacobs, Tal Linzen, Marten van Schijndel:
Proceedings of the 8th Workshop on Cognitive Modeling and Computational Linguistics, CMCL 2018, Salt Lake City, Utah, USA, January 7, 2018. Association for Computational Linguistics 2018, ISBN 978-1-948087-10-0 [contents] - [i2]Marten van Schijndel, Tal Linzen:
A Neural Model of Adaptation in Reading. CoRR abs/1808.09930 (2018) - [i1]Marten van Schijndel, Tal Linzen:
Can Entropy Explain Successor Surprisal Effects in Reading? CoRR abs/1810.11481 (2018) - 2017
- [c12]Marten van Schijndel, William Schuler:
Approximations of Predictive Entropy Correlate with Reading Times. CogSci 2017 - [e2]Ted Gibson, Tal Linzen, Asad B. Sayeed, Marten van Schijndel, William Schuler:
Proceedings of the 7th Workshop on Cognitive Modeling and Computational Linguistics, CMCL@EACL 2017, Valencia, Spain, April 3, 2017. Association for Computational Linguistics 2017, ISBN 978-1-945626-38-8 [contents] - 2016
- [c11]Marten van Schijndel, William Schuler:
Addressing surprisal deficiencies in reading time models. CL4LC@COLING 2016 2016: 32-37 - [c10]Cory Shain, Marten van Schijndel, Richard Futrell, Edward Gibson, William Schuler:
Memory access during incremental sentence processing causes reading time latency. CL4LC@COLING 2016 2016: 49-58 - 2015
- [c9]Marten van Schijndel, Brian Murphy, William Schuler:
Evidence of syntactic working memory usage in MEG data. CMCL@NAACL-HLT 2015: 79-88 - [c8]Marten van Schijndel, William Schuler:
Hierarchic syntax improves reading time prediction. HLT-NAACL 2015: 1597-1605 - [c7]Evan Jaffe, Lifeng Jin, David King, Marten van Schijndel:
AZMAT: Sentence Similarity Using Associative Matrices. SemEval@NAACL-HLT 2015: 159-163 - [e1]Tim O'Donnell, Marten van Schijndel:
Proceedings of the 6th Workshop on Cognitive Modeling and Computational Linguistics, CMCL@NAACL-HLT 2015, Denver, CO, USA, June 4, 2015. Association for Computational Linguistics 2015, ISBN 978-1-941643-42-6 [contents] - 2014
- [c6]Marten van Schijndel, Micha Elsner:
Bootstrapping into Filler-Gap: An Acquisition Story. ACL (1) 2014: 1084-1093 - [c5]Marten van Schijndel, William Schuler, Peter W. Culicover:
Frequency effects in the processing of unbounded dependencies. CogSci 2014 - 2013
- [j1]Marten van Schijndel, Andrew Exley, William Schuler:
A Model of Language Processing as Hierarchic Sequential Prediction. Top. Cogn. Sci. 5(3): 522-540 (2013) - [c4]Marten van Schijndel, Luan Nguyen, William Schuler:
An Analysis of Memory-based Processing Costs using Incremental Deep Syntactic Dependency Parsing. CMCL 2013: 37-46 - [c3]Marten van Schijndel, William Schuler:
An Analysis of Frequency- and Memory-Based Processing Costs. HLT-NAACL 2013: 95-105 - 2012
- [c2]Marten van Schijndel, Andrew Exley, William Schuler:
Connectionist-Inspired Incremental PCFG Parsing. CMCL@NAACL-HLT 2012: 51-60 - [c1]Luan Nguyen, Marten van Schijndel, William Schuler:
Accurate Unbounded Dependency Recovery using Generalized Categorial Grammars. COLING 2012: 2125-2140
Coauthor Index
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last updated on 2024-09-26 01:56 CEST by the dblp team
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