Multimodal Decoupling for Diversified Recommendation through Semantic and Structural Shaping
Recommender systems often suffer from over-concentrated results when optimized for accuracy, limiting recommendation diversity. While diversity has become an important objective, existing methods still face fundamental limitations from both semantic and structural perspectives. On the one hand, multimodal recommender systems provide rich semantic signals, yet are often treated as auxiliary to ID embeddings, leading to ineffective semantic utilization for diversity. On the other hand, the accuracy--diversity trade-off persists during training, where accuracy gains often come at the cost of diversity. We show that this phenomenon is fundamentally governed by both the structural properties o...
| Authors | Changran He, Jiaming Wei, Jianghong Ma et al. |
|---|---|
| Primary category | cs.IR |
| Published | 19 October 2026 |
| Last updated at source | 19 October 2026 |
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