Article

Agentic AI and LLM-Driven Framework for Contextual Anomaly Detection

2026-06-28

Abstract excerpt

The rapid proliferation of autonomous LLM-based agents in high-stakes enterprise and operational environments has created a critical safety gap: these agents generate multi-step action plans that can fail through contextual misalignment, structural incoherence, or adversarial manipulation, yet traditional anomaly detection methods remain ill-equipped to address these novel failure modes. Conventional approaches—wh...

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Literature Corpus work: 59c3498c-8012-5e6a-93e1-3a1a730868fe
DOI: 10.14293/pr2199.003969.v1

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