Abstract: Generating accurate SQL from users’ natural language questions (text-to-SQL) remains a long-standing challenge due to the complexities involved in user question understanding, database ...
Bridging the Question–Answer Gap in Retrieval-Augmented Generation: Hypothetical Prompt Embeddings
Abstract: Retrieval-Augmented Generation (RAG) systems synergize retrieval mechanisms with generative language models to enhance the accuracy and relevance of responses. However, bridging the style ...
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