A new real-world benchmark shows RAG and continual learning methods fail at continuous knowledge drift in LLMs due to forgetting and inconsistency, while a time-aware retrieval baseline using event evolution graphs improves consistency.
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RAG or Learning? Understanding the Limits of LLM Adaptation under Continuous Knowledge Drift in the Real World
A new real-world benchmark shows RAG and continual learning methods fail at continuous knowledge drift in LLMs due to forgetting and inconsistency, while a time-aware retrieval baseline using event evolution graphs improves consistency.