mlsanityData to 7 Oct 2026

ProAgent: From Robotic Process Automation to Agentic Process Automation

arXiv 2311.10751 ↗First posted 2 Nov 2023cs.RO cs.AI cs.CLcited by 26

On the map: LLM agents and tool use → Software engineering coding agents

Abstract (arXiv)

From ancient water wheels to robotic process automation (RPA), automation technology has evolved throughout history to liberate human beings from arduous tasks. Yet, RPA struggles with tasks needing human-like intelligence, especially in elaborate design of workflow construction and dynamic decision-making in workflow execution. As Large Language Models (LLMs) have emerged human-like intelligence, this paper introduces Agentic Process Automation (APA), a groundbreaking automation paradigm using LLM-based agents for advanced automation by offloading the human labor to agents associated with construction and execution. We then instantiate ProAgent, an LLM-based agent designed to craft workflows from human instructions and make intricate decisions by coordinating specialized agents. Empirical experiments are conducted to detail its construction and execution procedure of workflow, showcasing the feasibility of APA, unveiling the possibility of a new paradigm of automation driven by agents. Our code is public at https://github.com/OpenBMB/ProAgent.

Key facts. Cited by 26 papers in the map (data through 7 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 35 of its 50 references that are in the map. First posted on arXiv 2 Nov 2023.

Builds on

35 of 50 references.

References · 35

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  2. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,072
  3. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,500
  4. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,155
  5. 2022Emergent Abilities of Large Language Modelscited by 2,483
  6. 2022Do As I Can, Not As I Say: Grounding Language in Robotic Affordancescited by 2,302
  7. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,203
  8. 2023Voyager: An Open-Ended Embodied Agent with Large Language Modelscited by 2,081
  9. 2022Survey of Hallucination in Natural Language Generationcited by 2,056
  10. 2023ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIscited by 1,880
  11. 2021WebGPT: Browser-assisted question-answering with human feedbackcited by 1,722
  12. 2023The Rise and Potential of Large Language Model Based Agents: A Surveycited by 1,422
23 more
  1. 2023Gorilla: Large Language Model Connected with Massive APIscited by 1,302
  2. 2022WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agentscited by 1,197
  3. 2022Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agentscited by 1,029
  4. 2020On Faithfulness and Factuality in Abstractive Summarizationcited by 895
  5. 2023Graph of Thoughts: Solving Elaborate Problems with Large Language Modelscited by 873
  6. 2023Reasoning with Language Model is Planning with World Modelcited by 846
  7. 2023Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Modelscited by 695
  8. 2023AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviorscited by 580
  9. 2023Cognitive Architectures for Language Agentscited by 422
  10. 2023Tool Learning with Foundation Modelscited by 302
  11. 2023Large Language Models as Tool Makerscited by 293
  12. 2023WebCPM: Interactive Web Search for Chinese Long-form Question Answeringcited by 93
  13. 2023Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Modelscited by 92
  14. 2023Rational Decision-Making Agent with Internalized Utility Judgmentcited by 11
  15. 2020Robotic Process Automation -- A Systematic Literature Review and Assessment Frameworkcited by 9
  16. 2020From Robotic Process Automation to Intelligent Process Automation: Emerging Trendscited by 8
  17. 2020On the Evaluation of Intelligent Process Automationcited by 6
  18. 2020Towards Intelligent Robotic Process Automation for BPMerscited by 5
  19. 2020Multipurpose Intelligent Process Automation via Conversational Assistantcited by 4
  20. 2020D3BA: A Tool for Optimizing Business Processes Using Non-Deterministic Planningcited by 4
  21. 2020Monte Carlo Tree Search for Generating Interactive Data Analysis Interfacescited by 2
  22. 2020Automated Discovery of Data Transformations for Robotic Process Automationcited by 1
  23. 2020Automatic Business Process Structure Discovery using Ordered Neurons LSTM: A Preliminary Studycited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 14; 2025: 4; 2026: 7.

26 papers.

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By area:

  1. 2024OpenHands: An Open Platform for AI Software Developers as Generalist Agentscited by 956
  2. 2024Large Language Model-Brained GUI Agents: A Surveycited by 160
  3. 2024ScreenAgent: A Vision Language Model-driven Computer Control Agentcited by 101
  4. 2024RepoAgent: An LLM-Powered Open-Source Framework for Repository-level Code Documentation Generationcited by 69
  5. 2024Agent Planning with World Knowledge Modelcited by 66
  6. 2024KnowAgent: Knowledge-Augmented Planning for LLM-Based Agentscited by 61
  7. 2024FlowBench: Revisiting and Benchmarking Workflow-Guided Planning for LLM-based Agentscited by 39
  8. 2024Benchmarking Agentic Workflow Generationcited by 36
  9. 2025MPO: Boosting LLM Agents with Meta Plan Optimizationcited by 36
  10. 2024WorkflowLLM: Enhancing Workflow Orchestration Capability of Large Language Modelscited by 28
  11. 2026From Static Templates to Dynamic Runtime Graphs: A Survey of Workflow Optimization for LLM Agentscited by 22
  12. 2025A Goal Without a Plan Is Just a Wish: Efficient and Effective Global Planner Training for Long-Horizon Agent Taskscited by 17
14 more
  1. 2024Automating the Enterprise with Foundation Modelscited by 14
  2. 2023Towards Responsible Generative AI: A Reference Architecture for Designing Foundation Model based Agentscited by 13
  3. 2024MAO: A Framework for Process Model Generation with Multi-Agent Orchestrationcited by 8
  4. 2024Frontier AI Ethics: Anticipating and Evaluating the Societal Impacts of Language Model Agentscited by 5
  5. 2024A Taxonomy of Architecture Options for Foundation Model-based Agents: Analysis and Decision Modelcited by 4
  6. 2024Explainable Behavior Cloning: Teaching Large Language Model Agents through Learning by Demonstrationcited by 4
  7. 2025LawFlow: Collecting and Simulating Lawyers' Thought Processes on Business Formation Case Studiescited by 2
  8. 2026The Energy Footprint of LLM-Based Environmental Analysis: LLMs and Domain Productscited by 2
  9. 2026PolicyGuide: From Guarding One Action to Guiding the Whole Workflow for Policy-Compliant LLM Agentscited by 2
  10. 2025Are LLM Agents the New RPA? A Comparative Study with RPA Across Enterprise Workflowscited by 1
  11. 2026POLARIS: Typed Planning and Governed Execution for Agentic AI in Back-Office Automationcited by 1
  12. 2026Foundation-Model-Based Agents in Industrial Automation: Purposes, Capabilities, and Open Challengescited by 1
  13. 2026Software Engineering for and with GUI Agentcited by 1
  14. 2026Beyond Generalist LLMs: Specialist Agentic Systems for Structured Code Workflow Executioncited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025A Survey on Agent Workflow -- Status and Future
  2. 2025A Practical Guide for Designing, Developing, and Deploying Production-Grade Agentic AI Workflows
  3. 2024AutoFlow: Automated Workflow Generation for Large Language Model Agents
  4. 2025FlowAgent: Achieving Compliance and Flexibility for Workflow Agents
  5. 2023Enhancing Trust in LLM-Based AI Automation Agents: New Considerations and Future Challenges
  6. 2024BMW Agents -- A Framework For Task Automation Through Multi-Agent Collaboration
  7. 2026Characterizing Large Language Model Agentic Workflows: A Study on N8n Ecosystem
  8. 2025Empowering Real-World: A Survey on the Technology, Practice, and Evaluation of LLM-driven Industry Agents