Fine-Tuning LLaMA for Multi-Stage Text Retrieval

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Discover how fine-tuning LLaMA models enhances text retrieval efficiency and accuracy
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This study explores enhancing text retrieval using state-of-the-art LLaMA models. Fine-tuned as RepLLaMA and RankLLaMA, these models achieve superior effectiveness for both passage and document retrieval, leveraging their ability to handle longer contexts and exhibiting strong zero-shot performance.