Score: 3

ReasonGraph: Visualisation of Reasoning Paths

Published: March 6, 2025 | arXiv ID: 2503.03979v1

By: Zongqian Li, Ehsan Shareghi, Nigel Collier

Potential Business Impact:

Shows how smart computer programs think step-by-step.

Business Areas:
Natural Language Processing Artificial Intelligence, Data and Analytics, Software

Large Language Models (LLMs) reasoning processes are challenging to analyze due to their complexity and the lack of organized visualization tools. We present ReasonGraph, a web-based platform for visualizing and analyzing LLM reasoning processes. It supports both sequential and tree-based reasoning methods while integrating with major LLM providers and over fifty state-of-the-art models. ReasonGraph incorporates an intuitive UI with meta reasoning method selection, configurable visualization parameters, and a modular framework that facilitates efficient extension. Our evaluation shows high parsing reliability, efficient processing, and strong usability across various downstream applications. By providing a unified visualization framework, ReasonGraph reduces cognitive load in analyzing complex reasoning paths, improves error detection in logical processes, and enables more effective development of LLM-based applications. The platform is open-source, promoting accessibility and reproducibility in LLM reasoning analysis.

Country of Origin
🇬🇧 🇦🇺 United Kingdom, Australia

Repos / Data Links

Page Count
7 pages

Category
Computer Science:
Computation and Language