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cs.CL2026
SynAE: A Framework for Measuring the Quality of Synthetic Data for Tool-Calling Agent Evaluations
Shuaiqi Wang, Aadyaa Maddi, Zinan Lin +1
Today, tool-calling agents are commonly evaluated or tested on static datasets of execution traces, including input commands, agent responses, and associated tool calls. However, i…
cs.SE2026
Measuring the Permission Gate: A Stress-Test Evaluation of Claude Code's Auto Mode
Zimo Ji, Zongjie Li, Pingchuan Ma +3
Claude Code's auto mode is the first deployed permission system for AI coding agents, using a two-stage transcript classifier to gate dangerous tool calls. Anthropic reports a 0.4%…
cs.CR2026
ClawLess: A Security Model of AI Agents
Hongyi Lu, Nian Liu, Shuai Wang +1
Autonomous AI agents powered by Large Language Models can reason, plan, and execute complex tasks, but their ability to autonomously retrieve information and run code introduces si…