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Transparency in artificial intelligence has become a question of provenance. Provenance tells you where a piece of content came from; it does not tell you why what it asserts was decided.
A number with no recorded reason may end up deciding for a patient Read More »
Sequential recommendation is a central task in recommender systems, and recent research has increasingly shifted toward generative recommenders that leverage both sequential patterns and semantic item information. However, these methods are often evaluated on a small set of widely used benchmarks. This raises a natural question: do these benchmarks actually require the advanced modeling capabilities
In this survey, we connect several lines of work from the pre-neural and neural era, by showing how hybrid approaches of words and characters as well as subword-based approaches based on learned segmentation have been proposed and evaluated. We conclude that there is and likely will never be a silver bullet singular solution for all
