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WeMM-Embedding is a family of universal multimodal embedding models developed by Tencent, achieving state-of-the-art performance in retrieval and recommendation tasks for WeChat applications, with variants in 2B, 4B, and 9B parameters released publicly.
LightOn releases DenseOn and LateOn, a new generation of open state-of-the-art single and multi-vector retrieval models that outperform existing ones.