--- title: "Who cites How to Compute the Probability of — 36 citing papers" description: "36 papers of the Elamur Research library cite «How to Compute the Probability of a Word», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/pimentel-2024-how-compute-probability-word/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/pimentel-2024-how-compute-probability-word/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [How to Compute the Probability of a Word](https://md.research.elamur.ai/free/en/papers/pimentel-2024-how-compute-probability-word/) / cited by # Who cites «How to Compute the Probability of a Word» 36 papers of our library cite it (of the 149,439 whose bibliographies we read) · 15 with a page here, the most cited first · [← back to «How to Compute the Probability of a Word»](https://md.research.elamur.ai/free/en/papers/pimentel-2024-how-compute-probability-word/) 1. **[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* 2. **[The Impact of Token Granularity on the Predictive Power of Language Model Surprisal](https://md.research.elamur.ai/free/en/papers/oh-2025-impact-token-granularity-predictive-power/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Byung-Doh Oh, William Schuler*2025 · 12 citations* 3. **[Child-Directed Language Does Not Consistently Boost Syntax Learning in Language Models](https://md.research.elamur.ai/free/en/papers/padovani-2025-child-directed-language-does-not/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Francesca Padovani, Jaap Jumelet, Yevgen Matusevych, et al.*2025 · 9 citations* 4. [**Exact Byte-Level Probabilities from Tokenized Language Models for FIM-Tasks and Model Ensembles arXiv:2410.09303**Buu Phan, Brandon Amos, Itai Gat, et al.*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/phan-2024-exact-byte-level-probabilities-tokenized/) 5. **[Tokenisation is NP-Complete](https://md.research.elamur.ai/free/en/papers/whittington-2025-tokenisation-is-np-complete/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Philip Whittington, Gregor Bachmann, Tiago Pimentel*2025 · 4 citations* 6. **[An Existence Proof for Neural Language Models That Can Explain Garden-Path Effects via Surprisal](https://md.research.elamur.ai/free/en/papers/yoshida-2026-existence-proof-neural-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ryo Yoshida, Shinnosuke Isono, Taiga Someya, et al.*2026 · 1 citation* 7. **[Clozing the Gap: Exploring Why Language Model Surprisal Outperforms Cloze Surprisal](https://md.research.elamur.ai/free/en/papers/nair-2026-clozing-gap-exploring-why-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sathvik Nair, Byung-Doh Oh*2026 · 1 citation* 8. **[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* 9. **[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* 10. **[Surprisal Dynamics for the Detection of Multi-Word Expressions in English](https://md.research.elamur.ai/free/en/papers/alves-2025-surprisal-dynamics-detection-multi-word/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Diego Alves, Sergei Bagdasarov, Elke Teich*2025 · 1 citation* 11. **[The Frequency Confound in Language-Model Surprisal and Metaphor Novelty](https://md.research.elamur.ai/free/en/papers/momen-2026-frequency-confound-language-model-surprisal/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Omar Momen, Sina Zarrieß*2026* 12. **[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* 13. **[Word predictability estimates from language models are not robust to tokenizer vocabulary](https://md.research.elamur.ai/free/en/papers/nguyen-2026-word-predictability-estimates-language-models/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Kien Nguyen, Suhas Arehalli*2026* 14. **[Word Surprisal Correlates with Sentential Contradiction in LLMs](https://md.research.elamur.ai/free/en/papers/shi-2026-word-surprisal-correlates-sentential-contradiction/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Ning Shi, Bradley Hauer, David Basil, et al.*2026* 15. [**Assessing the Agreement Competence of Large Language Models**Alba Táboas García, Leo Wanner*2025*](https://md.research.elamur.ai/free/en/papers/garcia-2025-assessing-agreement-competence-large-language/) 21 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/pimentel-2024-how-compute-probability-word/) — How to Compute the Probability of a Word