31 citations · 36 across the 7 of their papers we have counts for
3 papers · 1 filter
GRAM: Generative Recommendation via Semantic-aware Multi-granular Late Fusion
Sunkyung Lee, Minjin Choi, Eunseong Choi +2
Generative recommendation is an emerging paradigm that leverages the extensive knowledge of large language models by formulating recommendations into a text-to-text generation task…
DIFF: Dual Side-Information Filtering and Fusion for Sequential Recommendation
Hye-young Kim, Minjin Choi, Sunkyung Lee +2
Side-information Integrated Sequential Recommendation (SISR) benefits from auxiliary item information to infer hidden user preferences, which is particularly effective for sparse i…
Why is Normalization Necessary for Linear Recommenders?
Seongmin Park, Mincheol Yoon, Hye-young Kim +1
Despite their simplicity, linear autoencoder (LAE)-based models have shown comparable or even better performance with faster inference speed than neural recommender models. However…