SHAPE: Unifying Safety, Helpfulness and Pedagogy for Educational LLMs
Large Language Models (LLMs) have been widely explored in educational scenarios. We identify a critical vulnerability in current educational LLMs, pedagogical jailbreaks, where students use answer-inducing prompts to elicit solutions rather than scaffolded instructions. To enable systematic study, we unify and formalize safe, helpful, and pedagogical behaviors with a knowledge-mastery graph and introduce SHAPE, a benchmark of 9,087 student-question pairs for evaluating tutoring behavior under adversarial pressure. We propose a graph-augmented tutoring pipeline that infers prerequisite concepts from queries, identifies mastery gaps, and routes generation between instructing and problem-sol...
| Authors | Sihang Zhao, Kangrui Yu, Youliang Yuan et al. |
|---|---|
| Primary category | cs.CL |
| Published | 24 April 2026 |
| Last updated at source | 24 April 2026 |
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