EMNLP Findings2023
The Linearity of the Effect of Surprisal on Reading Times across Languages
Weijie Xu, Jason Chon, Tianran Liu, Richard Futrell
Abstract
In psycholinguistics, surprisal theory posits that the amount of online processing effort expended by a human comprehender per word positively correlates with the surprisal of that word given its preceding context. In addition to this overall correlation, more importantly, the specific quantitative form taken by the processing effort as a function of surprisal offers insights into the underlying cognitive mechanisms of language processing. Focusing on English, previous studies have looked into the linearity of surprisal on reading times. Here, we extend the investigation by examining eyetracking corpora of seven languages: Danish, Dutch, English, German, Japanese, Mandarin, and Russian. We find evidence for superlinearity in some languages, but the results are highly sensitive to which language model is used to estimate surprisal.
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Cited by top-tier papers6
- The Impact of Token Granularity on the Predictive Power of Language Model SurprisalByung-Doh Oh, William SchulerACL 2025 · 7 citations
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- Clozing the Gap: Exploring Why Language Model Surprisal Outperforms Cloze SurprisalSathvik Nair, Byung-Doh OhACL 2026 · 1 citation
- Genre Matters: How Text Types Interact with Decoding Strategies and Lexical Predictors in Shaping Reading BehaviorLena Sophia Bolliger, Lena Ann JägerEMNLP 2025
- Memory efficiency and resource-rational encoding in sentence processingWeijie Xu, Brian Dillon, Richard FutrellACL 2026
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