# Visualization Biases MLLM's Decision Making in Network Data Tasks

arXiv: https://arxiv.org/abs/2511.03617 · HTML: https://mlsanity.com/paper/2511.03617/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 18 references that are in the map.
- First posted on arXiv 5 Nov 2025.

## Builds on (most cited first, 8 of 8)

- [Large Language Models in Finance: A Survey](https://mlsanity.com/paper/2311.10723/) (2023)
- [Large Language Models in Law: A Survey](https://mlsanity.com/paper/2312.03718/) (2023)
- [A Survey of Large Language Models in Medicine: Progress, Application, and Challenge](https://mlsanity.com/paper/2311.05112/) (2023)
- [Surfacing Visualization Mirages](https://mlsanity.com/paper/2001.02316/) (2020)
- [SmartGD: A GAN-Based Graph Drawing Framework for Diverse Aesthetic Goals](https://mlsanity.com/paper/2206.06434/) (2022)
- [Multicriteria Scalable Graph Drawing via Stochastic Gradient Descent, (SGD)2](https://mlsanity.com/paper/2112.01571/) (2021)
- [Narrating Networks](https://mlsanity.com/paper/1801.01322/) (2018)
- [GraphTrials: Visual Proofs of Graph Properties](https://mlsanity.com/paper/2409.02907/) (2024)

## Abstract (arXiv)

We evaluate how visualizations can influence the judgment of MLLMs about the presence or absence of bridges in a network. We show that the inclusion of visualization improves confidence over a structured text-based input that could theoretically be helpful for answering the question. On the other hand, we observe that standard visualization techniques create a strong bias towards accepting or refuting the presence of a bridge -- independently of whether or not a bridge actually exists in the network. While our results indicate that the inclusion of visualization techniques can effectively influence the MLLM's judgment without compromising its self-reported confidence, they also imply that practitioners must be careful of allowing users to include visualizations in generative AI applications so as to avoid undesired hallucinations.