Secure Retrieval-Augmented Generation against Poisoning Attacks
NeutralArtificial Intelligence
Recent advancements in large language models (LLMs) have significantly enhanced natural language processing, leading to innovative applications. However, the introduction of Retrieval-Augmented Generation (RAG) has raised concerns about security, particularly regarding data poisoning attacks that can compromise the integrity of these systems. Understanding these risks and developing effective defenses is crucial for ensuring the reliability of LLMs in various applications.
— Curated by the World Pulse Now AI Editorial System

