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In this chapter, we introduce a novel model-agnostic approach, termed Semantic-Guided Feature Distillation (SGFD for short), which can robustly extract effective recommendation-oriented features from generic multimodal features using the teacher-student framework.

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Semantic-Guided Feature Distillation for Multimodal Recommendation

  • 章节

  • 发表日期：

    2025年

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  • Fan Liu,
  • Zhenyang Li,
  • Liqiang Nie

摘要

In this chapter, we introduce a novel model-agnostic approach, termed Semantic-Guided Feature Distillation (SGFD for short), which can robustly extract effective recommendation-oriented features from generic multimodal features using the teacher-student framework.