Evren Gurkan-Cavusoglu

Assessing LLMs for Serendipity Discovery in Knowledge Graphs: A Case for Drug Repurposing

Large Language Models (LLMs) have greatly advanced knowledge graph question answering (KGQA), yet existing systems are typically optimized for returning highly relevant but predictable answers. A missing yet desired capacity is to exploit LLMs to suggest surprise and novel ("serendipitious") answer