Trustworthiness in Retrieval-Augmented Generation Systems: A Survey

Understand

Retrieval-Augmented Generation (RAG) has quickly grown into a pivotal paradigm in the development of Large Language Models (LLMs).

• Although existing research mainly emphasizes accuracy and efficiency, the trustworthiness of RAG systems remains insufficiently explored.
• RAG can improve LLM reliability by grounding responses in external and up-to-date knowledge, reducing hallucinations.
• However, unreliable retrieval or improper knowledge utilization may still lead to undesirable outputs.