Risk-Aware Introspective RAG (RAI-RAG) is a safety-aligned RAG framework integrating introspective reasoning, risk-aware retrieval gating, and secure evidence filtering to build trustworthy, robust, and secure LLM and agentic AI systems.
trustworthy-ai safety-alignment retrieval-augmented-generation-rag agentic-ai-security llm-security-compliance-prompt-injection ai-safety-research risk-aware-ai introspective-reasoning
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Updated
Mar 7, 2026 - Python