AI RESEARCH
Architecture Matters: Comparing RAG Systems under Knowledge Base Poisoning
arXiv CS.LG
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ArXi:2605.05632v1 Announce Type: cross Retrieval-Augmented Generation (RAG) systems are vulnerable to knowledge base poisoning, yet existing attacks have been evaluated almost exclusively against vanilla retrieve-then-generate pipelines. Architectures designed to handle conflicting retrieved information - multi-agent debate, agentic retrieval, recursive language models - remain untested against adversarially optimized contradictions.