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Matching Matters: A Fair Quality-Efficiency Benchmark for Command-Line Agents
Rapid advances in large language models have improved the task-solving capabilities of command-line-interface (CLI)-based agents, whose CLIs determine how models invoke tools, maintain interaction history, and recover from failures. Consequently, effective matching between CLIs and LLMs has become e
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