AgentSPEX is a new language and harness for explicitly specifying and running structured LLM-agent workflows with typed steps, control flow, parallel execution, and a visual editor.
Architecting resilient llm agents: A guide to secure plan-then-execute implementations
4 Pith papers cite this work, alongside 1 external citations. Polarity classification is still indexing.
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citation-polarity summary
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2026 4roles
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background 1representative citing papers
Parallax enforces structural separation between AI thinking and acting via independent multi-tier validation, information flow control, and state rollback, blocking 98.9% of 280 adversarial attacks with zero false positives even when the reasoning system is fully compromised.
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%.
A three-agent mobile system for end-to-end walking support shows motivational companion dialogue boosts affect and UX in a 12-person in-the-wild crossover study.
citing papers explorer
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AgentSPEX: An Agent SPecification and EXecution Language
AgentSPEX is a new language and harness for explicitly specifying and running structured LLM-agent workflows with typed steps, control flow, parallel execution, and a visual editor.
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Parallax: Why AI Agents That Think Must Never Act
Parallax enforces structural separation between AI thinking and acting via independent multi-tier validation, information flow control, and state rollback, blocking 98.9% of 280 adversarial attacks with zero false positives even when the reasoning system is fully compromised.
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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%.
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SmartWalkCoach: An AI Companion for End-to-End Walking Guidance, Motivation, and Reflection
A three-agent mobile system for end-to-end walking support shows motivational companion dialogue boosts affect and UX in a 12-person in-the-wild crossover study.