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February 27, 2024Open Access

Understanding Retrieval Pitfalls: Challenges Faced by Retrieval Augmented Generation (RAG) models

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Abstract

Improving the performance and application of Large Language Models Author Amanda Kau (ORCID: 0009-0004-4949-9284) Large language models (LLMs) like GPT-4, the engine of products like ChatGPT, have taken centre stage in recent years due to their astonishing capabilities. Yet, they are far from perfect.

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Amanda Kau (2024) studied this question.

synapsesocial.com/papers/68e7779db6db6435876ec40a https://doi.org/10.59350/wek8b-sbj84

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Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Retrieval-Augmented Generation for Natural Language Processing: A Survey2024 · 78 citations
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4RAGged Edges: The Double-Edged Sword of Retrieval-Augmented Chatbots2024 · 6 citations
5Retrieval-Augmented Generation (RAG) with LLMs: Architecture, Methodology, System Design, Limitations, and Outcomes2025

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