Author

Jun-Jie Zhou

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Preprint Aug 2026

WeMM-Embedding: WeChat Multi-Modal Embedding Technical Report

WeMM-Embedding is presented, a family of universal multimodal embedding models supporting text, images, videos, visual documents, and arbitrarily interleaved multimodal inputs with flexible output dimensions and achieves leading performance on multiple public benchmarks.

Jun-Jie Zhou, Ke Mei, Lei Li et al. · 11 citations

Preprint Aug 2026

Geo-Embed: Towards Unified Multimodal Embeddings for Urban Understanding

This work introduces GeoMEB, a large-scale multimodal embedding benchmark that standardizes 45 urban evaluation tasks across retrieval, visual question answering, change detection, classification, and visual grounding, and presents Geo-Embed, a unified embedding model that adapts a shared vision-language backbone to in...

Jia-Peng Li, Yong Li, Jun-Jie Zhou et al. · 0 citations