2023
DOI: 10.1016/j.jml.2022.104400
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Number feature distortion modulates cue-based retrieval in reading

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Cited by 10 publications
(7 citation statements)
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“…. , the ungrammatical word were is now much less surprising than in a setting where the preamble is always represented veridically (Yadav et al, 2023). Similarly, in a missing VP sentence like The apartment that the maid who the cleaning service sent over was well-decorated, if the preamble is edited to contain only two as opposed to three subject nouns, not encountering a third verb would not be surprising to the reader (Futrell et al, 2020;Hahn et al, 2022).…”
Section: Model Comparisons Via Cross-validationmentioning
confidence: 99%
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“…. , the ungrammatical word were is now much less surprising than in a setting where the preamble is always represented veridically (Yadav et al, 2023). Similarly, in a missing VP sentence like The apartment that the maid who the cleaning service sent over was well-decorated, if the preamble is edited to contain only two as opposed to three subject nouns, not encountering a third verb would not be surprising to the reader (Futrell et al, 2020;Hahn et al, 2022).…”
Section: Model Comparisons Via Cross-validationmentioning
confidence: 99%
“…The current implementation of the noisy-channel proposal as an MPT model is considerably less detailed than the ones provided by Hahn et al (2022) and Yadav et al (2023), as it neither takes into account the size of the required edits, nor the corpus frequencies of the different constructions. On the other hand, it is, to my knowledge, the first implementation that takes into account both distortions and repairs across grammatical, ungrammatical, and illusion sentences.…”
Section: Delpdmentioning
confidence: 99%
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“…Similarly, self-organizing theories predict that local interactions between strings of words can interfere with the formation of the overall structure of the sentence, especially when the local string is semantically coherent (Smith et al, 2021). At present, our results do not adjudicate between these theories, and quantitative model comparisons (see Paape & Vasishth, 2022;Yadav et al, 2023, for examples) will be necessary to determine which theories best explain the overall pattern of local coherence effects.…”
Section: What's Driving the Semantic Effect?mentioning
confidence: 48%
“…For this reason, the present evaluation should be seen rather as a proof-of-concept rather than a comprehensive evaluation. Such an evaluation would require significant amounts of benchmark data (for examples of such extensive evaluations, see Engelmann et al, 2020;Nicenboim et al, 2020;Yadav et al, 2023) and must be left for future work. Table 2, and Figures 7 and 8 show that the predictions for the experimental effects of animacy (semantic interference) and subjecthood (syntactic interference) in the experimental data are generally more in agreement with SEAM than with SWIFT: the violin plots in Figure 7 from SEAM have a better overlap than the observed data than the predictions from SWIFT.…”
Section: Experimental Effects Of Memory Interferencementioning
confidence: 99%