Accommodate Knowledge Conflicts in Retrieval-augmented LLMs: Towards Robust Response Generation in the Wild
The episode discusses how Retrieval-augmented LLMs must handle contradictory information sources. Instead of averaging conflicting facts, the system must analyze relationships between data points to maintain transparency. The goal is to build robust AI that flags ambiguities, maps contradictions using conflict graphs, and prompts users on which source should be prioritized.