BobFlow: Towards Human-Agent Collaborative Data Science Using Dataflows

BobFlow proposes using dataflows as a shared computational abstraction to facilitate human-agent collaboration in data science, combining this with the ReAct paradigm to allow agents to iteratively build and run dataflows while analysts can inspect and provide feedback. The system demonstrates that analysts can better understand, inspect, and verify agent-generated analyses, and experimental results show accuracy gains of up to 18.6 points at roughly one‑third the inference cost of a script‑based ReAct agent.

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• llms
• agents
• data-engineering