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RAG systems are not just enhanced by external knowledge; they are also vulnerable to targeted attacks that can compromise accuracy, privacy, and fairness.
Dialectal variations can degrade LLM performance by over 6% in some cases, revealing a critical gap in their robustness to real-world language use.