Vector Quantization for Recommender Systems: A Review and Outlook
Vector quantization, renowned for its unparalleled feature compression capabilities, has
been a prominent topic in signal processing and machine learning research for several …
been a prominent topic in signal processing and machine learning research for several …
Distinguished Quantized Guidance for Diffusion-based Sequence Recommendation
W Mao, S Liu, H Liu, H Liu, X Li, L Hu - arxiv preprint arxiv:2501.17670, 2025 - arxiv.org
Diffusion models (DMs) have emerged as promising approaches for sequential
recommendation due to their strong ability to model data distributions and generate high …
recommendation due to their strong ability to model data distributions and generate high …
Toward next-generation AI-powered recommender systems: exploration of pretraining and generative approaches
Q Liu - 2024 - theses.lib.polyu.edu.hk
Recommender systems stand out as a prime example of machine learning's success,
designed to ease the decision-making process for users by automatically suggesting items …
designed to ease the decision-making process for users by automatically suggesting items …