ScholarSum introduces a hierarchical knowledge graph framework that emulates a student-teacher process for scientific summarization. It generates fluent, factually consistent summaries by first structuring documents into semantic units, then refining drafts through evidence retrieval and iterative review by a teacher-like component. Experiments show ScholarSum outperforms existing methods in completeness and factual faithfulness.