🔗 Who cites «On the Predictive Power of Neural Language Models for Human Real-Time Comprehension Behavior»

94 papers of our library cite it (of the 149,439 whose bibliographies we read) · 22 with a page here, the most cited first · ← back to «On the Predictive Power of Neural Language Models for Human Real-Time Comprehension Behavior»

1. 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
2. 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
3. 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
4. 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
5. 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
6. Can Language Models Handle Recursively Nested Grammatical Structures? A Case Study on Comparing Models and HumansComputational LinguisticsAndrew Lampinen2024 · 63 citations
7. How to Compute the Probability of a WordConference on Empirical Methods in Natural Language Processing (EMNLP)Tiago Pimentel, Clara Meister2024 · 38 citations
8. 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
9. Expectations over Unspoken Alternatives Predict Pragmatic InferencesJennifer Hu, Roger Levy, Judith Degen, et al.2023 · 27 citations
10. 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
11. 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
12. Language Models as Models of LanguagearXiv:2408.07144Raphael Milliere2024 · 21 citations
13. Predicting scalar diversity with context-driven uncertainty over alternativesWorkshop on Cognitive Modeling and Computational Linguistics (CMCL)Jennifer Hu, Roger Levy, Sebastian Schuster2022 · 19 citations
14. 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
15. 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
16. Probing for Reading TimesAnnual Meeting of the Association for Computational Linguistics (ACL)Eleftheria Tsipidi, Samuel Kiegeland, Francesco Ignazio Re, et al.2026 · 1 citation
17. 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
18. 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
19. Quantifying the cross-linguistic effects of syncretism on agreement attractionSociety for Computation in Linguistics (SCiL)Utku Turk, Eva Neu2026
20. 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
21. Toward Cognitive Alignment in Large Language Models: Integrating Linguistic Theory and Human DataWorkshop on Cognitive Modeling and Computational Linguistics (CMCL)Wajdi Zaghouani2026
22. Towards A Scanpath-Conditioned Surprisal Theory: Modeling Reader Information StatesAnnual Meeting of the Association for Computational Linguistics (ACL)Michael Mooney, Edmond S. L. Ho2026

72 more papers of our library cite it; they have no page here yet.

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