SourceArXiv AI•Stalecollected in 5h
A-R Space Profiles Tool-Using LLM Agents
#agent-safety#behavioral-profiling#autonomy-scaffoldsa-r-behavioral-spacearxivllm
💡New A-R framework profiles LLM agent safety in org deployments
⚡ 30-Second TL;DR
What Changed
Introduces A-R space with Action Rate, Refusal Signal, and Divergence metrics
Why It Matters
Offers a nuanced view for deploying LLM agents in organizations with varying risk tolerances. Highlights how scaffolds redistribute execution vs. refusal, aiding model selection.
What To Do Next
Profile your tool-using LLM agents using A-R metrics across autonomy scaffolds.
Who should care:Researchers & Academics
Key Points
- •Introduces A-R space with Action Rate, Refusal Signal, and Divergence metrics
- •Evaluates across Control, Gray, Dilemma, Malicious regimes and direct/planning/reflection autonomy
- •Reflection scaffolding boosts refusal in risk-laden contexts, varying by model
- •Enables observable behavioral profiles over scalar safety scores
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Original source: ArXiv AI ↗
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