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WeMM-Embedding: WeChat Multi-Modal Embedding Technical Report

60 upvotes · 25 AUG 2026 · Junjie Zhou, Ke Mei, Lei Li et al.

This paper introduces WeMM-Embedding, a family of universal multimodal embedding models that can represent various types of data in a shared space, enabling applications like retrieval, recommendation, and classification. Practitioners might care because WeMM-Embedding achieves state-of-the-art performance on multiple benchmarks and has been deployed at scale in real-world applications.

multimodal embeddingsuniversal embeddingsvisual documentsvisual-language modelscontinual learning