Are RAG-Enhanced LLMs Really Safe? Think Again!

Author(s): Harshmeet Singh Chandhok

Originally published on Towards AI.

Are RAG-Enhanced LLMs Really Safe? Think Again!

That’s what the hype says. On the surface, this sounds like a perfect fix by grounding the model in facts, and then hallucinations would vanish.

The article discusses the safety concerns surrounding RAG-enhanced language models, emphasizing that while they enable the integration of real-time data, they introduce significant risks such as garbage in, garbage out, adversarial attacks, continued hallucinations, data leakage, and prompt injection threats. Each risk is illustrated with examples and suggestions for mitigation strategies, ultimately arguing that RAG systems must be approached with caution and require robust handling to prevent misinformation and security vulnerabilities.

Read the full blog for free on Medium.

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Published via Towards AI