ConflictQA exposes LLM knowledge conflict failures

The so-called "AI rationalization trap" reveals that chain-of-thought reasoning breaks down when retrieved context contradicts itself.

• –The benchmark specifically tests conflicts between unstructured text and structured data (KGs), a common pain point in modern RAG
• –Evaluated models tended to become hypersensitive to prompting choices and over-relied on either text or KGs exclusively
• –The proposed XoT (explanation-based thinking) framework offers an architectural approach to force models to weigh heterogeneous evidence
• –This highlights a critical limitation for enterprise RAG: adding more sources doesn't improve accuracy if the model can't reconcile the disagreements