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ChEmbed: Enhancing Chemical Literature Search Through Domain-Specific Text Embeddings
Retrieval-Augmented Generation (RAG) systems in chemistry heavily depend on accurate and relevant retrieval of chemical literature. However, general-purpose text embedding models frequently fail to adequately represent complex chemical terminologies, resulting in suboptimal retrieval quality. Existi
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