Graph-of-Thought: Utilizing Large Language Models to Solve Complex and Dynamic Business Problems
On the map: LLM reasoning → Reasoning for agents, planning and code
Abstract (arXiv)
This paper presents Graph-of-Thought (GoT), a new model for workflow automation that enhances the flexibility and efficiency of Large Language Models (LLMs) in complex task execution. GoT advances beyond traditional linear and tree-like cognitive models with a graph structure that enables dynamic path selection. The open-source engine GoTFlow demonstrates the practical application of GoT, facilitating automated, data-driven decision-making across various domains. Despite challenges in complexity and transparency, GoTFlow's potential for improving business processes is significant, promising advancements in both efficiency and decision quality with continuous development.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning. Builds on 7 of its 17 references that are in the map. First posted on arXiv 10 Jan 2024.
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7 of 17 references.
Closest ancestors · 2
Same direction, newest first
- 2023Reasoning with Language Model is Planning with World Model24 May
- 2023Teaching Large Language Models to Self-Debug11 Apr
Other references · 5
- 2020Language Models are Few-Shot Learnerscited by 32,199
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
- 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,304
- 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,155
- 2022Faithful Reasoning Using Large Language Modelscited by 130
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- 2024WorkflowLLM: Enhancing Workflow Orchestration Capability of Large Language Models
- 2023Large Language Models can accomplish Business Process Management Tasks
- 2026GraphMind: From Operational Traces to Self-Evolving Workflow Automation
- 2024Re-Thinking Process Mining in the AI-Based Agents Era
- 2026Generating Workflow DAGs from Natural Language with Non-Reasoning LLMs
- 2024Benchmarking Agentic Workflow Generation
- 2026Large Language Models to Enhance Business Process Modeling: Past, Present, and Future Trends
- 2026Graph-Based Agentic AI with LangGraph: Workflow Pathways for Long-Running Stateful Business Processes