AI RESEARCH
AgentCollab: A Self-Evaluation-Driven Collaboration Paradigm for Efficient LLM Agents
arXiv CS.CL
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ArXi:2603.26034v1 Announce Type: new Autonomous agents powered by large language models (LLMs) perform complex tasks through long-horizon reasoning and tool interaction, where a fundamental trade-off arises between execution efficiency and reasoning robustness. Models at different capability-cost levels offer complementary advantages: lower-cost models enable fast execution but may struggle on difficult reasoning segments, while stronger models provide robust reasoning at higher computational cost.