DEPO formulates detector-evasive paraphrasing as a constrained MDP and solves it via Lagrangian primal-dual RL with GRPO-style updates to achieve evasion while satisfying a semantic-preservation constraint.
Hipo: Instruction hierarchy via constrained reinforcement learning
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
No existing AI security framework covers a majority of the 193 identified multi-agent system threats in any category, with OWASP Agentic Security Initiative achieving the highest overall coverage at 65.3%.
citing papers explorer
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Detector-Evasive LLM Paraphrasing via Constrained Policy Optimization
DEPO formulates detector-evasive paraphrasing as a constrained MDP and solves it via Lagrangian primal-dual RL with GRPO-style updates to achieve evasion while satisfying a semantic-preservation constraint.
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Security Considerations for Multi-agent Systems
No existing AI security framework covers a majority of the 193 identified multi-agent system threats in any category, with OWASP Agentic Security Initiative achieving the highest overall coverage at 65.3%.