Mohammad Kachuee, Phu Mon Htut, Sheng Li, Nikolaos Pappas, Miguel Ballesteros Martinez, Yassine Benajiba, Sujith Ravi, Dan Roth · 2026 · arXiv
DOI: 10.48550/arXiv.2610.28397 · open-access PDF
Agentic AI는 대규모 언어 모델(LLM)을 응답 생성에서 복잡한 워크플로스를 계획하고 실행하는 데까지 확장하여 유틸리티를 크게 확장하면서 애플리케이션을 불안정한 행동, 정보 유출 및 적대적 조작에 노출시킵니다.Multi-agent systems further expands these capabilities through specialization and collaboration, but distributed authority, heterogeneous roles, and opaque or potentially compromised participants make safeguarding even more challenging.
Machine translation (Meta M2M100); the English original follows.
Agentic AI extends large language models (LLMs) from generating responses to planning and executing complex workflows, substantially expanding their utility while exposing applications to unsafe actions, information leakage, and adversarial manipulation. Multi-agent systems further expand these capabilities through specialization and collaboration, but distributed authority, heterogeneous roles, and opaque or potentially compromised participants make safeguarding even more challenging. Existing defenses address important individual threats but provide fragmented coverage across local execution
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