In particular, we focus on estimating latent user preferences through implicit feedback while simultaneously predicting the contents of the reviews themselves.
given an item that a user hasn't yet interacted with, our goals are to (a) generate a plausible review, in order to estimate the user's nuanced reaction to the product; (b) estimate whether the user would be likely to interact with the product, based on their learned latent attributes; and (c) rank existing reviews using the language model, in order to surface 'meaningful' reviews to the user.