---
title: "Who cites On the Predictive Power of Neural — 94 citing papers"
description: "94 papers of the Elamur Research library cite «On the Predictive Power of Neural Language Models for Human Real-Time Comprehension…"
canonical: "https://research.elamur.ai/free/en/papers/wilcox-2020-predictive-power-neural-language-models/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wilcox-2020-predictive-power-neural-language-models/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [On the Predictive Power of Neural Language Models…](https://md.research.elamur.ai/free/en/papers/wilcox-2020-predictive-power-neural-language-models/) / cited by

# 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»](https://md.research.elamur.ai/free/en/papers/wilcox-2020-predictive-power-neural-language-models/)

1. **[Why Does Surprisal From Larger Transformer-Based Language Models Provide a Poorer Fit to Human Reading Times?](https://md.research.elamur.ai/free/en/papers/oh-2023-why-does-surprisal-larger-transformer/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Byung-Doh Oh, William Schuler*2023 · 211 citations*
2. [**Language models show human-like content effects on reasoning tasks arXiv:2207.07051**Ishita Dasgupta, Andrew K. Lampinen, Stephanie C. Y. Chan, et al.*2022 · 162 citations*](https://md.research.elamur.ai/free/en/papers/dasgupta-2022-language-models-show-human-like/)
3. **[Testing the Predictions of Surprisal Theory in 11 Languages](https://md.research.elamur.ai/free/en/papers/wilcox-2023-testing-predictions-surprisal-theory-11/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ethan G. Wilcox, Tiago Pimentel, Clara Meister, et al.*2023 · 159 citations*
4. **[Revisiting the Uniform Information Density Hypothesis](https://md.research.elamur.ai/free/en/papers/meister-2021-revisiting-uniform-information-density-hypothesis/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/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 benchmarks](https://md.research.elamur.ai/free/en/papers/truong-2023-language-models-naysayers-analysis-language/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**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 Humans](https://md.research.elamur.ai/free/en/papers/lampinen-2024-can-language-models-handle-recursively/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Andrew Lampinen*2024 · 63 citations*
7. **[How to Compute the Probability of a Word](https://md.research.elamur.ai/free/en/papers/pimentel-2024-how-compute-probability-word/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tiago Pimentel, Clara Meister*2024 · 38 citations*
8. **[Large Language Models Are Human-Like Internally](https://md.research.elamur.ai/free/en/papers/kuribayashi-2025-large-language-models-are-human/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tatsuki Kuribayashi, Yohei Oseki, Souhaib Ben Taieb, et al.*2025 · 30 citations*
9. [**Expectations over Unspoken Alternatives Predict Pragmatic Inferences**Jennifer Hu, Roger Levy, Judith Degen, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-expectations-over-unspoken-alternatives-predict/)
10. **[Filtered Corpus Training (FiCT) Shows that Language Models Can Generalize from Indirect Evidence](https://md.research.elamur.ai/free/en/papers/patil-2024-filtered-corpus-training-fict-shows/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Abhinav Patil, Jaap Jumelet, Yu Ying Chiu, et al.*2024 · 23 citations*
11. **[On the Proper Treatment of Tokenization in Psycholinguistics](https://md.research.elamur.ai/free/en/papers/giulianelli-2024-proper-treatment-tokenization-psycholinguistics/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mario Giulianelli, Luca Malagutti, Juan Luis Gastaldi, et al.*2024 · 23 citations*
12. [**Language Models as Models of Language arXiv:2408.07144**Raphael Milliere*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/milliere-2024-language-models-models-language/)
13. **[Predicting scalar diversity with context-driven uncertainty over alternatives](https://md.research.elamur.ai/free/en/papers/hu-2022-predicting-scalar-diversity-context-driven/) [Workshop on Cognitive Modeling and Computational Linguistics (CMCL)](https://md.research.elamur.ai/free/en/venues/cmcl/)**Jennifer Hu, Roger Levy, Sebastian Schuster*2022 · 19 citations*
14. **[Are Frequent Phrases Directly Retrieved like Idioms? An Investigation with Self-Paced Reading and Language Models](https://md.research.elamur.ai/free/en/papers/rambelli-2023-are-frequent-phrases-directly-retrieved/) [Workshop on Multiword Expressions (MWE)](https://md.research.elamur.ai/free/en/venues/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 Models](https://md.research.elamur.ai/free/en/papers/thamma-2026-human-like-fleeting-memory-improves/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Abishek Thamma, Micha Heilbron*2026 · 1 citation*
16. **[Probing for Reading Times](https://md.research.elamur.ai/free/en/papers/tsipidi-2026-probing-reading-times/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/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 Datasets](https://md.research.elamur.ai/free/en/papers/momen-2026-surprisal-metaphor-novelty-judgments-moderate/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Omar Momen, Emilie Sitter, Berenike Herrmann, et al.*2026 · 1 citation*
18. **[On the Effect of Hyperparameters in Language Modeling for Computational Linguistics](https://md.research.elamur.ai/free/en/papers/ning-2026-effect-hyperparameters-language-modeling-computational/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruoxi Ning, Yongpeng Zhu, Qingcheng Zeng, et al.*2026*
19. **[Quantifying the cross-linguistic effects of syncretism on agreement attraction](https://md.research.elamur.ai/free/en/papers/turk-2026-quantifying-cross-linguistic-effects-syncretism/) [Society for Computation in Linguistics (SCiL)](https://md.research.elamur.ai/free/en/venues/scil/)**Utku Turk, Eva Neu*2026*
20. **[Similar Predictions, Different Processes: A Multi-Level Comparison of Human and Multimodal LLM Language Prediction](https://md.research.elamur.ai/free/en/papers/wang-2026-similar-predictions-different-processes-multi/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Shuqi Wang, Zhenguang Cai*2026*
21. **[Toward Cognitive Alignment in Large Language Models: Integrating Linguistic Theory and Human Data](https://md.research.elamur.ai/free/en/papers/zaghouani-2026-cognitive-alignment-large-language-models/) [Workshop on Cognitive Modeling and Computational Linguistics (CMCL)](https://md.research.elamur.ai/free/en/venues/cmcl/)**Wajdi Zaghouani*2026*
22. **[Towards A Scanpath-Conditioned Surprisal Theory: Modeling Reader Information States](https://md.research.elamur.ai/free/en/papers/mooney-2026-scanpath-conditioned-surprisal-theory-modeling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michael Mooney, Edmond S. L. Ho*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/wilcox-2020-predictive-power-neural-language-models/) — On the Predictive Power of Neural Language Models for Human Real-Time Comprehension Behavior