KNIGHT: Knowledge Graph-Driven Multiple-Choice Question Generation with Adaptive Hardness Calibration

Ali Nemati6 days ago27 sec read21 views

KNIGHT is an LLM-based framework that uses knowledge graphs to efficiently generate multiple-choice question datasets for various subjects, allowing for controlled difficulty levels and multi-hop questions without re-feeding full source texts. This method reduces costs and time in creating assessment datasets while maintaining high quality across several evaluation criteria, making it a valuable tool for content creators looking to evaluate large language models effectively.

Read the full article at arXiv cs.CL (NLP)

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