Rag2 Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting https://arxiv.org/abs/2407.08223 Speculative RAG: Enhancing Retrieval Augmented Generation through DraftingRetrieval augmented generation (RAG) combines the generative abilities of large language models (LLMs) with external knowledge sources to provide more accurate and up-to-date responses. Recent RAG advancements focus on improving retrieval outcomes througharxiv.org0. AbstractRAG는 LLM의 생성 기능과.. 2025. 1. 22. Retrieval-Augmented Generation for Large Language Models: A Survey (1) Retrieval-Augmented Generation for Large Language Models: A SurveyLarge Language Models (LLMs) showcase impressive capabilities but encounter challenges like hallucination, outdated knowledge, and non-transparent, untraceable reasoning processes. Retrieval-Augmented Generation (RAG) has emerged as a promising solution byarxiv.org0. AbstractLLM(Large Language Model)은 뛰어난 성과를 보이지만, hallucination, .. 2024. 11. 11. 이전 1 다음