AI RESEARCH

State-Dependent Safety Failures in Multi-Turn Language Model Interaction

arXiv CS.AI

ArXi:2603.15684v1 Announce Type: cross Safety alignment in large language models is typically evaluated under isolated queries, yet real-world use is inherently multi-turn. Although multi-turn jailbreaks are empirically effective, the structure of conversational safety failure remains insufficiently understood. In this work, we study safety failures from a state-space perspective and show that many multi-turn failures arise from structured contextual state evolution rather than isolated prompt vulnerabilities. We.