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Microsoft has released E5-V, the first universal embedding model in the E5 family, which leverages a multimodal large language model (LLM) as its backbone. This new model adapts multimodal LLMs for universal embeddings using text-only training, outperforming traditional methods while reducing costs. The E5-V model addresses semantic understanding limitations and cold-start issues, showing promising advancements in general visual and language understanding. The paper also discusses hybrid item tokenization and progressive optimization.
Microsoft just released E5-V, the first universal embedding model in the E5 family, using a multimodal LLM as its backbone. Let's have a quick dive into the paper and highlight our favorite tidbits: 🧵📖 https://t.co/E8hgZ4Zo5W
E5-V: Universal Embeddings with Multimodal Large Language Models Adapts multimodal LLMs for universal embeddings using text-only training, outperforming traditional methods while reducing costs. 📝https://t.co/LplHO1qZg2 👨🏽💻https://t.co/YWAJij5zao https://t.co/Pqldeb7m4z
E5-V Universal Embeddings with Multimodal Large Language Models Multimodal large language models (MLLMs) have shown promising advancements in general visual and language understanding. However, the representation of multimodal information using MLLMs remains largely unexplored.… https://t.co/gOXn9dUtCI
