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Argus: A General-Purpose Agentic Runtime for Long-Horizon Reasoning
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Argus is an agentic runtime system that manages long-horizon reasoning tasks through persistent state and self-evolution, achieving 78% on SWE-Bench Pro versus 59% for Direct Copilot.
- 为何重要
- Software engineers building AI agent systems should care when they need reliable multi-step task execution with recovery from failures and the ability to learn from experience without retraining models.
- 注意
- Argus uses 1.41 times more aggregate tokens than baselines and requires operator-owned escalation points, meaning it trades computational efficiency for reliability and control in complex reasoning tasks.
收听本摘要
- agent
- agentic
- reasoning
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