Setting up a classical DLRM at work, show of hands: who has managed to bridge the gap to generative recommenders or LRMs?<p>Our survey identified quite a substantial list of challenges: product cardinality (Semantic IDs?), low performance vs discriminative recommenders (our user intents are heavily biases towards repetitive products), cold starts, entity features, missing explainability suite, training cost, prediction cost, etc.<p>Has anyone done it easily? Where is the tutorial for generative recommenders ?