# Multimodal Embedding Learning

UniME is a general embedding learning framework based on multimodal large models, significantly enhancing multimodal embedding capabilities through text discriminative knowledge distillation and hard negative sample-enhanced instruction tuning strategies.

UniME is a general embedding learning model based on a multimodal large model, trained with 336×336 image resolution and ranked first on the MMEB leaderboard.