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CASEL: Consequence-Aware Selective Execution for Reliable Long-Horizon Tool-Using Agents

arXiv cs.AI ↗ · 2026-10-28 Cached

论文提出 CASEL(Consequence-Aware Selective Execution Layer),一种模型无关的运行时分配策略,通过综合校准失败概率、后果严重性、可逆性、歧义性和证据新鲜度来为工具调用选择执行、验证、沙箱、澄清、审批或放弃等模式,仿真结果显示其将有害副作用轨迹比例从 14.75% 降至 7.02%。

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