Douyin Multimodal Embedding Model Technical Report
Multimodal representation learning is a cornerstone of modern AI. By encoding multimodal queries and targets into vectors, it powers industrial search and recommendation and underpins modern agents. Real-world platforms with complex modalities and massive-scale content, such as Douyin, Xiaohongshu, and YouTube, demand both efficiency under billion-scale indexing and fine-grained discrimination for hard matching. Existing MLLM embedding models rarely satisfy both. Contrastive models are efficient but rely on pair-level supervision too coarse for fine-grained distinctions, while CoT-based models improve discrimination through explicit generation impractical to serve online. We present Douyi...
| Authors | Haonan Chen, Chu Li, Zhicheng Wang et al. |
|---|---|
| Primary category | cs.IR |
| Published | 3 August 2026 |
| Last updated at source | 18 August 2026 |
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