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Interpretable Memory Models for Spaced Repetition

Year: 2026
Type: preprint
Abstract: Spaced repetition software schedules reviews with a memory model fit to review logs. Accuracy on a test set is not sufficient evidence of quality since available data are produced by existing schedulers, and new solutions must extrapolate beyond them. A model also needs a simple mechanistic interpretation. We present SBD, a model that is more interpretable and 80% smaller than the current state of the art at nearly the same accuracy.
Language: English
Open Access status: green
OpenAlex ID: W7212376546
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