一作ACL 2026Findings· Findings of ACL
D i FR a: A Unified Framework for Harmonizing Semantic Diversity and Factual Consistency in Question-Answer Generation
Zhenqin Li · ShengYong Ding · Shuangyin Li
摘要
Question-Answer Generation (QAG) is essential for alleviating the cold-start problem in domain-specific large language model (LLM) post-training, where high-quality data is severely scarce.Effective training samples include rich semantic diversity and rigorous factual consistency.Thus, it is nece...