Flowchart-Based Decision Making with Large Language Models

Large language models (LLMs) are widely used for conversational systems, but they face significant challenges in interpretability of dialogue flow and reproducibility of expert knowledge.To address this, we propose a novel method that extracts flowcharts from dialogue data and incorporates them into LLMs.This approach not only makes the decision-making process more interpretable through visual representation, but also ensures the reproducibility of expert knowledge by explicitly modeling structured reasoning flows.By evaluating on dialogue datasets, we demonstrate that our method effectively reconstructs expert decisionmaking paths with high precision and recall scores.These findings underscore the potential of flowchart-based decision making to bridge the gap between flexibility and structured reasoning, making chatbot systems more interpretable for developers and end-users.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.findings-acl.766
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
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article

Flowchart-Based Decision Making with Large Language Models

Tomoya Yamashita, Yuuki Yamanaka, Hiroshi Takahashi
Semantic Web and Ontologies
article

Flowchart-Based Decision Making with Large Language Models

Tomoya Yamashita, Yuuki Yamanaka, Hiroshi Takahashi
article en

Abstract

Large language models (LLMs) are widely used for conversational systems, but they face significant challenges in interpretability of dialogue flow and reproducibility of expert knowledge.To address this, we propose a novel method that extracts flowcharts from dialogue data and incorporates them into LLMs.This approach not only makes the decision-making process more interpretable through visual representation, but also ensures the reproducibility of expert knowledge by explicitly modeling structured reasoning flows.By evaluating on dialogue datasets, we demonstrate that our method effectively reconstructs expert decisionmaking paths with high precision and recall scores.These findings underscore the potential of flowchart-based decision making to bridge the gap between flexibility and structured reasoning, making chatbot systems more interpretable for developers and end-users.

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