mlsanityData to 14 Oct 2026

Local word statistics affect reading times independently of surprisal

arXiv 2103.04469 ↗First posted 7 Mar 2021cs.CL cs.LGcited by 3

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Abstract (arXiv)

Surprisal theory has provided a unifying framework for understanding many phenomena in sentence processing (Hale, 2001; Levy, 2008a), positing that a word's conditional probability given all prior context fully determines processing difficulty. Problematically for this claim, one local statistic, word frequency, has also been shown to affect processing, even when conditional probability given context is held constant. Here, we ask whether other local statistics have a role in processing, or whether word frequency is a special case. We present the first clear evidence that more complex local statistics, word bigram and trigram probability, also affect processing independently of surprisal. These findings suggest a significant and independent role of local statistics in processing. Further, it motivates research into new generalizations of surprisal that can also explain why local statistical information should have an outsized effect.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 2 of its 30 references that are in the map. First posted on arXiv 7 Mar 2021.

Builds on

2 of 30 references.

References · 2

  1. 2013One Billion Word Benchmark for Measuring Progress in Statistical Language Modelingcited by 308
  2. 2016Exploring the Limits of Language Modelingcited by 173

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 0; 2024: 1; 2025: 0; 2026: 1.

3 papers.