In sentence comprehension, what are the cognitive constraints that determine number agreement? Two broad classes of theoretical proposals are: (i) Representation distortion accounts, which assume that the number feature on the subject noun gets overwritten probabilistically by the number feature on a non-subject noun, leading to a non-veridical memory trace of the subject noun; and (ii) The cue-based retrieval account, which assumes that the features on the subject noun remain intact, and

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... sing difficulty is only a function of the memory constraints on dependency completion. However, both these classes of model fail to account for the full spectrum of number agreement patterns observed in published studies. Using 17 benchmark data sets on number agreement from four languages, we implement five computational models: two variants of representation distortion, the cue-based retrieval model, and two hybrid models that assume both representation distortion and retrieval. Quantitative model comparison decisively shows that the best fit is achieved by a hybrid model that assumes both feature distortion (specifically, feature percolation) and cue-based retrieval. More broadly, the work furnishes comprehensive evidence to support the idea that cue-based retrieval theory, which aims to be a general account of dependency completion, needs to incorporate a feature overwriting process.