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The GenAgent framework builds collaborative AI systems by creating workflows. The workflows are converted into code so that LLM agents can better understand them. GenAgent can learn from human-designed workflows and create new ones. The generated workflows can be interpreted as collaborative systems to complete complex tasks.
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Much previous AI research has focused on developing monolithic models to maximize their intelligence and capability, with the primary goal of enhancing performance on specific tasks. In contrast, this paper explores an alternative approach: collaborative AI systems that use workflows to integrate models, data sources, and pipelines to solve complex...
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