most citedEncode Me If You Can: Learning Universal User Representations via Event Sequence Autoencoding

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cs.IR2025★ 1 cited

Encode Me If You Can: Learning Universal User Representations via Event Sequence Autoencoding

Anton Klenitskiy, Artem Fatkulin, Daria Denisova +2

Building universal user representations that capture the essential aspects of user behavior is a crucial task for modern machine learning systems. In real-world applications, a use…

cs.IR2025

Sparse Autoencoders for Sequential Recommendation Models: Interpretation and Flexible Control

Anton Klenitskiy, Konstantin Polev, Daria Denisova +3

Many current state-of-the-art models for sequential recommendations are based on transformer architectures. Interpretation and explanation of such black box models is an important…