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Multimodal Generative Recommendation System
Multimodal Quantitative Language for Generative Recommendation
Published:2/20/2025
Multimodal Generative Recommendation SystemQuantitative Language Generation TasksKnowledge Transfer in Recommendation SystemsApplication of Pre-trained Language Models in RecommendationMultimodal Information Complementarity
This paper introduces MQL4GRec, a method that converts items from various domains and modalities into a unified 'quantitative language' to address cold start issues and knowledge transfer in recommendation systems, achieving NDCG improvements of up to 14.82% over baseline models.
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Multimodal Generative Recommendation for Fusing Semantic and Collaborative Signals
Published:10/8/2025
Multimodal Generative Recommendation SystemFusion of Collaborative and Semantic SignalsSelf-Supervised Quantization LearningSequential Recommender SystemsDINO Framework
The paper introduces MSCGRec, a generative recommendation system that addresses limitations in current sequential recommenders by integrating multiple semantic modalities and collaborative features. Empirical results show superior performance on three realworld datasets, validat
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