Diffusion-based Multi-modal Synergy Interest Network for Click-through Rate Prediction
In click-through rate prediction, click-through rate prediction is used to model users' interests. However, most of the existing CTR prediction methods are mainly based on the ID modality. As a result, they are unable to comprehensively model users' multi-modal preferences. Therefore, it is necessary to introduce multi-modal CTR prediction. Although it seems appealing to directly apply the existing multi-modal fusion methods to click-through rate prediction models, these methods (1) fail to effectively disentangle commonalities and specificities across different modalities; (2) fail to consider the synergistic effects between modalities and model the complex interactions between modalities.
Authors
- Zhuang Zhao
- Xiaoxi Cui
- Weihai Lu (ORCID: https://orcid.org/0009-0009-1783-5518)
- Yuepeng Li (ORCID: https://orcid.org/0000-0002-6874-866X)
- Yu Tong
Institutions
- Shanghai International Studies University (CN)
- Peking University (CN)
- Wuhan University (CN)
- Microsoft Research Asia (China) (CN)
- Takenaka (Japan) (JP)
Publication Details
- Published
- 2025-07-13
- DOI
- https://doi.org/10.1145/3726302.3729949
- Citations
- 5
- Primary Topic
- Recommender Systems and Techniques
- Type
- article
- Field-Weighted Citation Impact
- 16.23