Sam Boeve

Sam Boeve
Ghent University | UGhent · Department of Experimental Psychology

Master of Science
PhD researcher at Ghent University

About

9
Publications
832
Reads
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7
Citations
Introduction
I'm interested in the effects of word predictability during natural reading in atypical readers (i.e., children, people with dyslexia, L2, etc.). For this I make use of computational methods like large language models. Part of BogaertsLab: https://www.bogaertslab.com/
Education
September 2020 - July 2022
Ghent University
Field of study
  • Theoretical and Experimental Psychology
September 2017 - June 2020
Ghent University
Field of study
  • Theoretical and Experimental Psychology

Publications

Publications (9)
Preprint
Full-text available
Studies using computational estimates of word predictability from neural language models have garnered strong evidence in favour of surprisal theory. Upon encountering a word, readers experience a processing difficulty that is a linear function of that word’s surprisal. Evidence for this effect has been established in the English language or using...
Preprint
Full-text available
People need to often switch attention between external and internal sources of information, i.e., external and internal attention, respectively. There has been a recent surge of research interest in this type of attentional flexibility, which revealed that it is characterized by an asymmetrical cost, being larger for switching toward internal than...
Article
Despite the widely held belief that individual differences in statistical learning (SL) abilities are associated with linguistic skills, research has produced mixed results. To provide a comprehensive assessment of the literature, we conducted a meta-analysis of 97 studies examining the correlation between SL and linguistic abilities. Results revea...
Poster
Full-text available
Word predictability influences the processing difficulty a reader experiences. According to Surprisal theory (Levy, 2008) this causal bottleneck is a linear function of a word’s surprisal value: - log P(wt | w1, . . . , wt-1). Using LLMs to quantify the surprisal of words in text garnered widespread support for Surprisal theory (de Varda et al.,...
Article
Full-text available
Statistical learning is the ability to extract patterned information from continuous sensory signals. Recent evidence suggests that auditory-motor mechanisms play an important role in auditory statistical learning from speech signals. The question remains whether auditory-motor mechanisms support such learning generally or in a domain-specific mann...
Poster
Full-text available
Statistical learning (SL) is viewed as central to language acquisition and use. Studies using an individual differences approach (i.e., correlating SL and language ability), resulted in mixed evidence for this proposed link. Using a meta-analysis, we provide a comprehensive assessment of this SL-language link and potential moderators of this relati...
Preprint
Full-text available
Despite the widely held belief that individual differences in statistical learning (SL) abilities are associated with linguistic skills, research has produced mixed results. To provide a comprehensive assessment of the literature, we conducted a meta-analysis of 97 studies examining the correlation between SL and linguistic abilities. Results revea...

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