mlsanityData to 14 Oct 2026

ReasonGraph: Visualisation of Reasoning Paths

arXiv 2503.03979 ↗First posted 6 Mar 2025cs.CL cs.AI cs.HCcited by 6

On the map: LLM reasoning → Reasoning benchmarks and evaluation

Abstract (arXiv)

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.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 3 of its 17 references that are in the map. First posted on arXiv 6 Mar 2025.

Builds on

3 of 17 references.

References · 3

  1. 2024Prompt Compression for Large Language Models: A Surveycited by 67
  2. 2024500xCompressor: Generalized Prompt Compression for Large Language Modelscited by 47
  3. 2019Visualizing Attention in Transformer-Based Language Representation Modelscited by 8

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 4.

6 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2025Beyond the Black Box: Demystifying Multi-Turn LLM Reasoning with VISTA
  2. 2026When the Chain Breaks: Interactive Diagnosis of LLM Chain-of-Thought Reasoning Errors
  3. 2025Grounding LLM Reasoning with Knowledge Graphs
  4. 2024LLM Reasoners: New Evaluation, Library, and Analysis of Step-by-Step Reasoning with Large Language Models
  5. 2025Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models
  6. 2023GraphReason: Enhancing Reasoning Capabilities of Large Language Models through A Graph-Based Verification Approach
  7. 2023Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning
  8. 2026Graphionale: How Graph Visualizations of LLM Rationales Affect Human Decision Making