From Retrieval to Response: Tracing the Impact of Embedding Quality in RAG Systems
Recently, Retrieval Augmented Generation (RAG) has emerged as a powerful paradigm for enhancing the capability of Large Language Models (LLMs) by incorporating external, up-to-date, or domain-specific information through retrieval mechanisms. In their implementation, RAG systems usually rely on vect...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Assuntos: | |
| Acceso en liña: | https://ieeexplore.ieee.org/document/11300859/ |
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