DyKnow: Dynamically Verifying Time-Sensitive Factual Knowledge in LLMs

Understand

LLMs acquire knowledge from massive data snapshots collected at different timestamps.

• Their knowledge is then commonly evaluated using static benchmarks.
• However, factual knowledge is generally subject to time-sensitive changes, and static benchmarks cannot address those cases.
• We present an approach to dynamically evaluate the knowledge in LLMs and their time-sensitiveness against Wikidata, a publicly available up-to-date knowledge graph.