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Question-Aware Knowledge Graph Prompting for Enhancing Large Language Models
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This method enhances LLM performance in Multiple Choice Question Answering (MCQA) by generating query-adaptive soft prompts from Knowledge Graphs (KGs) during the inference stage. It integrates question embeddings into GNN aggregation (QNA) to assess KG relevance and uses global attention across answer options (GTP) to enrich soft prompt completeness, without requiring LLM fine-tuning.
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