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klotz: natural language processing* + instruction tuning* + retrieval-augmented generation*

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1. RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs

   A method that uses instruction tuning to adapt LLMs for knowledge-intensive tasks. RankRAG simultaneously trains the models for context ranking and answer generation, enhancing their retrieval-augmented generation (RAG) capabilities.

   2024-07-10 Tags: natural language processing, large language models, instruction tuning, context ranking, retrieval-augmented generation, nvidia, arxiv by klotz
2. NVIDIA Introduces RankRAG: Enhancing LLMs with Instruction Tuning

   NVIDIA and Georgia Tech researchers introduce RankRAG, a novel framework instruction-tuning a single LLM for top-k context ranking and answer generation. Aiming to improve RAG systems, it enhances context relevance assessment and answer generation.

   2024-07-10 Tags: rankrag, nvidia, llm, rag, instruction tuning, natural language processing by klotz

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