# A Neural Model of Adaptation in Reading

arXiv: https://arxiv.org/abs/1808.09930 · HTML: https://mlsanity.com/paper/1808.09930/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Aug 2018.

## Built on by (most cited first, 18 of 18)

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- [Dual Mechanism Priming Effects in Hindi Word Order](https://mlsanity.com/paper/2210.13938/) (2022)
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- [Patterns of Priming in Production: Lexical, Semantic and Structural Alignment in Language Model Generation](https://mlsanity.com/paper/2609.04484/) (2026)

## Abstract (arXiv)

It has been argued that humans rapidly adapt their lexical and syntactic expectations to match the statistics of the current linguistic context. We provide further support to this claim by showing that the addition of a simple adaptation mechanism to a neural language model improves our predictions of human reading times compared to a non-adaptive model. We analyze the performance of the model on controlled materials from psycholinguistic experiments and show that it adapts not only to lexical items but also to abstract syntactic structures.