AI RESEARCH
Learning to Conceal Risk: Controllable Multi-turn Red Teaming for LLMs in the Financial Domain
arXiv CS.LG
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ArXi:2509.10546v2 Announce Type: replace-cross Large Language Models (LLMs) are increasingly deployed in finance, where unsafe behavior can lead to serious regulatory risks. However, most red-teaming research focuses on overtly harmful content and overlooks attacks that appear legitimate on the surface yet induce regulatory-violating responses. We address this gap by