Aleksandr V. Petrov

gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative Sampling (Extended Abstract)

Sequential recommendation models predict the next item in a sequence of user-item interactions, akin to how language models predict the next tokens. These models often adapt language model architectures, treating item IDs as if they were token IDs. However, the number of potential items in recommend…