mlsanityData to 7 Oct 2026

Towards Responsible Generative AI: A Reference Architecture for Designing Foundation Model based Agents

arXiv 2311.13148 ↗First posted 22 Nov 2023cs.AI cs.SEcited by 13

On the map: LLM reasoning → Reasoning for agents, planning and code

also in 1 more
Abstract (arXiv)

Foundation models, such as large language models (LLMs), have been widely recognised as transformative AI technologies due to their capabilities to understand and generate content, including plans with reasoning capabilities. Foundation model based agents derive their autonomy from the capabilities of foundation models, which enable them to autonomously break down a given goal into a set of manageable tasks and orchestrate task execution to meet the goal. Despite the huge efforts put into building foundation model based agents, the architecture design of the agents has not yet been systematically explored. Also, while there are significant benefits of using agents for planning and execution, there are serious considerations regarding responsible AI related software quality attributes, such as security and accountability. Therefore, this paper presents a pattern-oriented reference architecture that serves as guidance when designing foundation model based agents. We evaluate the completeness and utility of the proposed reference architecture by mapping it to the architecture of two real-world agents.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning. Builds on 53 of its 67 references that are in the map. First posted on arXiv 22 Nov 2023.

Builds on

53 of 67 references.

Closest ancestors · 3

Same direction, newest first

  1. 2023Put Your Money Where Your Mouth Is: Evaluating Strategic Planning and Execution of LLM Agents in an Auction Arena9 Oct
  2. 2023Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate30 May
  3. 2023SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks27 May

Other references · 50

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  13. 2023SMART-LLM: Smart Multi-Agent Robot Task Planning using Large Language Modelscited by 151
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  18. 2023MetaAgents: Large Language Model Based Agents for Decision-Making on Teamingcited by 85
  19. 2023BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agentscited by 83
  20. 2023VELMA: Verbalization Embodiment of LLM Agents for Vision and Language Navigation in Street Viewcited by 67
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  22. 2023RCAgent: Cloud Root Cause Analysis by Autonomous Agents with Tool-Augmented Large Language Modelscited by 62
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  35. 2023An Empirical Study on Software Bill of Materials: Where We Stand and the Road Aheadcited by 7
  36. 2023A Taxonomy of Foundation Model based Systems through the Lens of Software Architecturecited by 6
  37. 2023SeeHow: Workflow Extraction from Programming Screencasts through Action-Aware Video Analyticscited by 4
  38. 2023QB4AIRA: A Question Bank for AI Risk Assessmentcited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 5; 2025: 4; 2026: 4.

13 papers.

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By area:

  1. 2024AgentOps: Enabling Observability of LLM Agentscited by 46
  2. 2024Agent Design Pattern Catalogue: A Collection of Architectural Patterns for Foundation Model based Agentscited by 35
  3. 2025Towards Trustworthy GUI Agents: A Surveycited by 33
  4. 2024Swiss Cheese Model for AI Safety: A Taxonomy and Reference Architecture for Multi-Layered Guardrails of Foundation Model Based Agentscited by 13
  5. 2025SHIELDA: Structured Handling of Exceptions in LLM-Driven Agentic Workflowscited by 12
  6. 2024A Taxonomy of Architecture Options for Foundation Model-based Agents: Analysis and Decision Modelcited by 4
  7. 2026Agentic Design Patterns: A System-Theoretic Frameworkcited by 4
  8. 2026Toward Architecture-Aware Evaluation Metrics for LLM Agentscited by 3
  9. 2024Responsible AI Question Bank: A Comprehensive Tool for AI Risk Assessmentcited by 2
  10. 2025AgentArcEval: An Architecture Evaluation Method for Foundation Model based Agentscited by 2
  11. 2025A Research Roadmap for Augmenting Software Engineering Processes and Software Products with Generative AIcited by 1
  12. 2026A Reference Architecture for Agentic Hybrid Retrieval in Dataset Searchcited by 1
1 more
  1. 2026Describing Agentic AI Systems with C4: Lessons from Industry Projectscited by 0

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  4. 2025Who is Responsible? The Data, Models, Users or Regulations? A Comprehensive Survey on Responsible Generative AI for a Sustainable Future
  5. 2026Developing LLM-based Multi-Agent Systems in Software Engineering: A Mixed-Method Experience Report
  6. 2026The Agent Use of Agent Beings: Agent Cybernetics Is the Missing Science of Foundation Agents
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