🧑‍🔬 Who cites Jon Gauthier

500 citations of their works from 436 papers of our library (of the 149,439 whose bibliographies we read) · 100 with a page here, the most cited first · ← Jon Gauthier

1. A Broad-Coverage Challenge Corpus for Sentence Understanding through InferenceConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Adina Williams, Nikita Nangia, Samuel R. Bowman2018 · 5,551 citations
2. A Structured Self-attentive Sentence EmbeddingarXiv:1703.03130Zhouhan Lin, Minwei Feng, Cicero Nogueira dos Santos, et al.2017 · 1,797 citations
3. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelsarXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5BvosjAarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.2022 · 1,756 citations
4. Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language InferenceR. Thomas McCoy, Ellie Pavlick, Tal Linzen2019 · 1,662 citations
5. Deep Biaffine Attention for Neural Dependency ParsingTimothy Dozat, Christopher D. Manning2016 · 1,326 citations
6. Long Short-Term Memory-Networks for Machine ReadingConference on Empirical Methods in Natural Language Processing (EMNLP)Jianpeng Cheng, Li Dong, Mirella Lapata2016 · 1,313 citations
7. DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language UnderstandingProceedings of the AAAI Conference on Artificial IntelligenceTao Shen, Tianyi Zhou, Guodong Long, et al.2017 · 854 citations
8. Breaking NLI Systems with Sentences that Require Simple Lexical InferencesMax Glockner, Vered Shwartz, Yoav Goldberg2018 · 525 citations
9. DyNet: The Dynamic Neural Network ToolkitarXiv:1701.03980Graham Neubig, Chris Dyer, Yoav Goldberg, et al.2017 · 489 citations
10. Experience Grounds LanguageConference on Empirical Methods in Natural Language Processing (EMNLP)Yonatan Bisk, Ari Holtzman, Jesse Thomason, et al.2020 · 439 citations
11. Neural Natural Language Inference Models Enhanced with External KnowledgeAnnual Meeting of the Association for Computational Linguistics (ACL)Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, et al.2018 · 315 citations
12. Good-Enough Compositional Data AugmentationAnnual Meeting of the Association for Computational Linguistics (ACL)Jacob Andreas2020 · 313 citations
13. Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for LittleConference on Empirical Methods in Natural Language Processing (EMNLP)Koustuv Sinha, Robin Jia, Dieuwke Hupkes, et al.2021 · 297 citations
14. SocialIQA: Commonsense Reasoning about Social InteractionsarXiv:1904.09728Maarten Sap, Hannah Rashkin, Derek Chen, et al.2019 · 259 citations
15. Charagram: Embedding Words and Sentences via Character n-gramsConference on Empirical Methods in Natural Language Processing (EMNLP)John Wieting, Mohit Bansal, Kevin Gimpel, et al.2016 · 242 citations
16. What Happens To BERT Embeddings During Fine-tuning?BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLPAmil Merchant, Elahe Rahimtoroghi, Ellie Pavlick, et al.2020 · 220 citations
17. Why Does Surprisal From Larger Transformer-Based Language Models Provide a Poorer Fit to Human Reading Times?Transactions of the Association for Computational Linguistics (TACL)Byung-Doh Oh, William Schuler2023 · 211 citations
18. What Artificial Neural Networks Can Tell Us About Human Language AcquisitionarXiv:2208.07998Alex Warstadt, Samuel R. Bowman2022 · 177 citations
19. Language Models as Agent ModelsFindings of the Association for Computational LinguisticsJacob Andreas2022 · 165 citations
20. BabyBERTa: Learning More Grammar With Small-Scale Child-Directed LanguageConference on Computational Natural Language Learning (CoNLL)Philip A. Huebner, Elior Sulem, Fisher Cynthia, et al.2021 · 164 citations
21. Language models show human-like content effects on reasoning tasksarXiv:2207.07051Ishita Dasgupta, Andrew K. Lampinen, Stephanie C. Y. Chan, et al.2022 · 162 citations
22. Testing the Predictions of Surprisal Theory in 11 LanguagesTransactions of the Association for Computational Linguistics (TACL)Ethan G. Wilcox, Tiago Pimentel, Clara Meister, et al.2023 · 159 citations
23. Do latent tree learning models identify meaningful structure in sentences?Transactions of the Association for Computational Linguistics (TACL)Adina Williams, Andrew Drozdov, Samuel R. Bowman2018 · 149 citations
24. Language Model Behavior: A Comprehensive SurveyComputational LinguisticsTyler A. Chang, Benjamin K. Bergen2024 · 148 citations
25. SyntaxGym: An Online Platform for Targeted Evaluation of Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jon Gauthier, Jennifer Hu, Ethan Wilcox, et al.2020 · 147 citations
26. A fine-grained comparison of pragmatic language understanding in humans and language modelsJennifer Hu, Sammy Floyd, Olessia Jouravlev, et al.2023 · 136 citations
27. UnNatural Language InferenceAnnual Meeting of the Association for Computational Linguistics (ACL)Koustuv Sinha, Prasanna Parthasarathi, Joelle Pineau, et al.2021 · 135 citations
28. Interpretable Neural Predictions with Differentiable Binary VariablesAnnual Meeting of the Association for Computational Linguistics (ACL)Jasmijn Bastings, Wilker Aziz, Ivan Titov2019 · 135 citations
29. Prompting is not a substitute for probability measurements in large language modelsConference on Empirical Methods in Natural Language Processing (EMNLP)Jennifer Hu, Roger Levy2023 · 133 citations
30. Revisiting the Uniform Information Density HypothesisConference on Empirical Methods in Natural Language Processing (EMNLP)Clara Meister, Tiago Pimentel, Patrick Haller, et al.2021 · 124 citations
31. Can Language Models Encode Perceptual Structure Without Grounding? A Case Study in ColorConference on Computational Natural Language Learning (CoNLL)Mostafa Abdou, Artur Kulmizev, Daniel Hershcovich, et al.2021 · 122 citations
32. How Much Do Language Models Copy From Their Training Data? Evaluating Linguistic Novelty in Text Generation Using RAVENTransactions of the Association for Computational Linguistics (TACL)R. Thomas McCoy, Paul Smolensky, Tal Linzen, et al.2023 · 117 citations
33. Neural Models of FactualityRachel Rudinger, Aaron Steven White, Benjamin Van Durme2018 · 112 citations
34. minicons: Enabling Flexible Behavioral and Representational Analyses of Transformer Language ModelsarXiv:2203.13112Kanishka Misra2022 · 102 citations
35. Simulating Action Dynamics with Neural Process NetworksarXiv:1711.05313Antoine Bosselut, Omer Levy, Ari Holtzman, et al.2017 · 102 citations
36. Frequency Effects on Syntactic Rule Learning in TransformersConference on Empirical Methods in Natural Language Processing (EMNLP)Jason Wei, Dan Garrette, Tal Linzen, et al.2021 · 92 citations
37. NL-Augmenter: A Framework for Task-Sensitive Natural Language AugmentationNorthern European Journal of Language TechnologyKaustubh Dhole, Varun Gangal, Sebastian Gehrmann, et al.2023 · 86 citations
38. ORCA: A Challenging Benchmark for Arabic Language UnderstandingFindings of the Association for Computational LinguisticsAbdelRahim Elmadany, ElMoatez Billah Nagoudi, Muhammad Abdul-Mageed2023 · 83 citations
39. Language models are not naysayers: An analysis of language models on negation benchmarksJoint Conference on Lexical and Computational Semantics (*SEM)Thinh Hung Truong, Timothy Baldwin, Karin Verspoor, et al.2023 · 78 citations
40. Structural Persistence in Language Models: Priming as a Window into Abstract Language RepresentationsTransactions of the Association for Computational Linguistics (TACL)Arabella Sinclair, Jaap Jumelet, Willem Zuidema, et al.2022 · 74 citations
41. CLiMP: A Benchmark for Chinese Language Model EvaluationConference of the European Chapter of the Association for Computational Linguistics (EACL)Beilei Xiang, Changbing Yang, Yu Li, et al.2021 · 73 citations
42. Transformer Grammars: Augmenting Transformer Language Models with Syntactic Inductive Biases at ScaleTransactions of the Association for Computational Linguistics (TACL)Laurent Sartran, Samuel Barrett, Adhiguna Kuncoro, et al.2022 · 72 citations
43. Mission: Impossible Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Julie Kallini, Isabel Papadimitriou, Richard Futrell, et al.2024 · 70 citations
44. Do Neural Language Representations Learn Physical Commonsense?arXiv:1908.02899Maxwell Forbes, Ari Holtzman, Yejin Choi2019 · 64 citations
45. Can Language Models Handle Recursively Nested Grammatical Structures? A Case Study on Comparing Models and HumansComputational LinguisticsAndrew Lampinen2024 · 63 citations
46. A Better Way to Do Masked Language Model ScoringAnnual Meeting of the Association for Computational Linguistics (ACL)Carina Kauf, Anna A. Ivanova2023 · 53 citations
47. How poor is the stimulus? Evaluating hierarchical generalization in neural networks trained on child-directed speechAnnual Meeting of the Association for Computational Linguistics (ACL)Aditya Yedetore, Tal Linzen, Robert Frank, et al.2023 · 49 citations
48. A Mention-Ranking Model for Abstract Anaphora ResolutionAna Marasović, Leo Born, Juri Opitz, et al.2017 · 43 citations
49. Arc-swift: A Novel Transition System for Dependency ParsingPeng Qi, Christopher D. Manning2017 · 39 citations
50. CausalGym: Benchmarking causal interpretability methods on linguistic tasksAnnual Meeting of the Association for Computational Linguistics (ACL)Aryaman Arora, Dan Jurafsky, Christopher Potts2024 · 38 citations
51. How to Compute the Probability of a WordConference on Empirical Methods in Natural Language Processing (EMNLP)Tiago Pimentel, Clara Meister2024 · 38 citations
52. BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language ModelsarXiv:2309.06085Wei Qi Leong, Jian Gang Ngui, Yosephine Susanto, et al.2023 · 33 citations
53. Probing Contextual Language Models for Common Ground with Visual RepresentationsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Gabriel Ilharco, Rowan Zellers, Ali Farhadi, et al.2021 · 33 citations
54. Large Language Models Are Human-Like InternallyTransactions of the Association for Computational Linguistics (TACL)Tatsuki Kuribayashi, Yohei Oseki, Souhaib Ben Taieb, et al.2025 · 30 citations
55. Log Probabilities Are a Reliable Estimate of Semantic Plausibility in Base and Instruction-Tuned Language ModelsarXiv:2403.14859Carina Kauf, Emmanuele Chersoni, Alessandro Lenci, et al.2024 · 29 citations
56. Expectations over Unspoken Alternatives Predict Pragmatic InferencesJennifer Hu, Roger Levy, Judith Degen, et al.2023 · 27 citations
57. Sensitivity as a Complexity Measure for Sequence Classification TasksTransactions of the Association for Computational Linguistics (TACL)Michael Hahn, Dan Jurafsky, Richard Futrell2021 · 26 citations
58. Filtered Corpus Training (FiCT) Shows that Language Models Can Generalize from Indirect EvidenceTransactions of the Association for Computational Linguistics (TACL)Abhinav Patil, Jaap Jumelet, Yu Ying Chiu, et al.2024 · 23 citations
59. On the Proper Treatment of Tokenization in PsycholinguisticsConference on Empirical Methods in Natural Language Processing (EMNLP)Mario Giulianelli, Luca Malagutti, Juan Luis Gastaldi, et al.2024 · 23 citations
60. Language Models as Models of LanguagearXiv:2408.07144Raphael Milliere2024 · 21 citations
61. Predicting scalar diversity with context-driven uncertainty over alternativesWorkshop on Cognitive Modeling and Computational Linguistics (CMCL)Jennifer Hu, Roger Levy, Sebastian Schuster2022 · 19 citations
62. Adversarial Analysis of Natural Language Inference SystemsarXiv:1912.03441Tiffany Chien, Jugal Kalita2019 · 15 citations
63. Causal Interventions Reveal Shared Structure Across English Filler–Gap ConstructionsSasha Boguraev, Christopher Potts, Kyle Mahowald2025 · 13 citations
64. Natural Language Processing RELIES on LinguisticsComputational LinguisticsJuri Opitz, Shira Wein, Nathan Schneider2025 · 13 citations
65. What Goes Into a LM Acceptability Judgment? Rethinking the Impact of Frequency and LengthConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Lindia Tjuatja, Graham Neubig, Tal Linzen, et al.2025 · 12 citations
66. From Language to Cognition: How LLMs Outgrow the Human Language NetworkConference on Empirical Methods in Natural Language Processing (EMNLP)Badr AlKhamissi, Greta Tuckute, Yingtian Tang, et al.2025 · 11 citations
67. Are Frequent Phrases Directly Retrieved like Idioms? An Investigation with Self-Paced Reading and Language ModelsWorkshop on Multiword Expressions (MWE)Giulia Rambelli, Emmanuele Chersoni, Marco S. G. Senaldi, et al.2023 · 11 citations
68. Can Language Models Learn Typologically Implausible Languages?Transactions of the Association for Computational Linguistics (TACL)Tianyang Xu, Tatsuki Kuribayashi, Yohei Oseki, et al.2026 · 10 citations
69. Targeted Syntactic Evaluation on the Chomsky HierarchyLanguage Resources and Evaluation Conference (LREC)Taiga Someya, Ryo Yoshida, Yohei Oseki2024 · 10 citations
70. Language Models Fail to Introspect About Their Knowledge of LanguagearXiv:2503.07513Siyuan Song, Jennifer Hu, Kyle Mahowald2025 · 9 citations
71. When Your Language Model Cannot Even Do Determiners Right: Probing for Anti-Presuppositions and the Maximize Presupposition! PrincipleJudith Sieker, Sina Zarrieß2023 · 9 citations
72. Can language models capture syntactic associations without surface cues? A case study of reflexive anaphor licensing in English control constructionsSoo-Hwan Lee, Sebastian Schuster2022 · 9 citations
73. TurkBench: A Benchmark for Evaluating Turkish Large Language ModelsWorkshop Natural Language Processing for Turkic LanguagesCagri Toraman, Ahmet Kaan Sever, Ayşe Aysu Cengiz, et al.2026 · 8 citations
74. Towards Fine-Grained Pedagogical Control over English Grammar Complexity in Educational Text GenerationDominik Glandorf, Detmar Meurers2024 · 7 citations
75. Acquiring Linguistic Knowledge from Multimodal InputConference on Computational Natural Language Learning (CoNLL)Theodor Amariucai, Alexander Scott Warstadt2023 · 6 citations
76. Are Formal and Functional Linguistic Mechanisms Dissociated in Language Models?Computational LinguisticsMichael Hanna, Yonatan Belinkov, Sandro Pezzelle2026 · 5 citations
77. Are BabyLMs Deaf to Gricean Maxims? A Pragmatic Evaluation of Sample-efficient Language ModelsBabyLM WorkshopRaha Askari, Sina Zarrieß, Özge Alacam, et al.2025 · 4 citations
78. Sparks of Pure Competence in LLMs: the Case of Syntactic Center Embedding in EnglishSociety for Computation in Linguistics (SCiL)Daniel Hardt2025 · 3 citations
79. Experimental Pragmatics with Machines: Testing LLM Predictions for the Inferences of Plain and Embedded DisjunctionsarXiv:2405.05776Polina Tsvilodub, Paul Marty, Sonia Ramotowska, et al.2024 · 3 citations
80. For GPT-4 as with Humans: Information Structure Predicts Acceptability of Long-Distance DependenciesarXiv:2505.09005Nicole Cuneo, Eleanor Graves, Supantho Rakshit, et al.2025 · 2 citations
81. Understanding Roles and Entities: Datasets and Models for Natural Language InferencearXiv:1904.09720Arindam Mitra, Ishan Shrivastava, Chitta Baral2019 · 2 citations
82. Do BabyLMs Wanna Learn Wanna Contraction? On the Learnability without Language-Specific BiasFindings of the Association for Computational LinguisticsKangsan Noh, Sanghoun Song2026 · 1 citation
83. Human-like Fleeting Memory Improves Language Learning but Impairs Reading Time Prediction in Transformer Language ModelsTransactions of the Association for Computational Linguistics (TACL)Abishek Thamma, Micha Heilbron2026 · 1 citation
84. Language Models Learn Constructional Semantics, Not To Mention Syntax: Investigating LM Understanding of Paired-Focus ConstructionsConference on Computational Natural Language Learning (CoNLL)Wesley Scivetti, Ethan Gotlieb Wilcox, Nathan Schneider, et al.2026 · 1 citation
85. Probing for Reading TimesAnnual Meeting of the Association for Computational Linguistics (ACL)Eleftheria Tsipidi, Samuel Kiegeland, Francesco Ignazio Re, et al.2026 · 1 citation
86. Surprisal and Metaphor Novelty Judgments: Moderate Correlations and Divergent Scaling Effects Revealed by Corpus-Based and Synthetic DatasetsConference of the European Chapter of the Association for Computational Linguistics (EACL)Omar Momen, Emilie Sitter, Berenike Herrmann, et al.2026 · 1 citation
87. Uniform Information Density and Syntactic Reduction: Revisiting *that*-Mentioning in English Complement ClausesConference on Empirical Methods in Natural Language Processing (EMNLP)Hailin Hao, Elsi Kaiser2025 · 1 citation
88. Mechanistic Interpretability Meets Cognitive Linguistics: Modelling Locative Image Schemas in the Circuit FrameworkLanguage Resources and Evaluation Conference (LREC)Mattia Proietti, Afra Alishahi, Grzegorz Chrupała, et al.2026
89. Memory efficiency and resource-rational encoding in sentence processingAnnual Meeting of the Association for Computational Linguistics (ACL)Weijie Xu, Brian Dillon, Richard Futrell2026
90. On the Effect of Hyperparameters in Language Modeling for Computational LinguisticsAnnual Meeting of the Association for Computational Linguistics (ACL)Ruoxi Ning, Yongpeng Zhu, Qingcheng Zeng, et al.2026
91. Open-access Dataset on Acceptability Ratings of Korean Clausal Constructions by Humans and GPT ModelsLanguage Resources and Evaluation Conference (LREC)Gyu-Ho Shin, Soo-Hwan Lee, Chanyoung Lee2026
92. Quantifying the cross-linguistic effects of syncretism on agreement attractionSociety for Computation in Linguistics (SCiL)Utku Turk, Eva Neu2026
93. Similar Predictions, Different Processes: A Multi-Level Comparison of Human and Multimodal LLM Language PredictionConference on Computational Natural Language Learning (CoNLL)Shuqi Wang, Zhenguang Cai2026
94. The Dog the Cat Chased Stumped the Model: Measuring When Language Models Abandon Structure for ShortcutsConference of the European Chapter of the Association for Computational Linguistics (EACL)Sangmitra Madhusudan, Kaige Chen, Ali Emami2026
95. Toward Cognitive Alignment in Large Language Models: Integrating Linguistic Theory and Human DataWorkshop on Cognitive Modeling and Computational Linguistics (CMCL)Wajdi Zaghouani2026
96. Towards A Scanpath-Conditioned Surprisal Theory: Modeling Reader Information StatesAnnual Meeting of the Association for Computational Linguistics (ACL)Michael Mooney, Edmond S. L. Ho2026
97. What Brain Data Adds to Language Model TrainingConference on Computational Natural Language Learning (CoNLL)Gabriele Merlin, Omer Moussa, Mariya Toneva2026
98. Assessing the Agreement Competence of Large Language ModelsAlba Táboas García, Leo Wanner2025
99. Is It JUST Semantics? A Case Study of Discourse Particle Understanding in LLMsWilliam Sheffield, Kanishka Misra, Valentina Pyatkin, et al.2025
100. Towards an Analysis of Discourse and Interactional Pragmatic Reasoning Capabilities of Large Language ModelsarXiv:2408.03074Amelie Robrecht, Judith Sieker, Clara Lachenmaier, et al.2024

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