VLM2Rec: Resolving Modality Collapse in Vision-Language Model Embedders for Multimodal Sequential Recommendation
VLM2Rec: Resolving Modality Collapse in Vision-Language Model Embedders for Multimodal Sequential Recommendation explores VLM2Rec enhances multimodal sequential recommendation by balancing modality utilization in Vision-Language Models.. Commercial viability score: 7/10 in Multimodal Recommendation.
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