Does visualization help AI understand data?

2025-07-24 · Victoria R. Li, Johnathan Sun, Martin Wattenberg arxiv

Charts and graphs help people analyze data, but can they also be useful to AI systems? To investigate this question, we perform a series of experiments with two commercial vision-language models: GPT 4.1 and Claude 3.5. Across three representative analysis tasks, the two systems describe synthetic datasets more precisely and accurately when raw data is accompanied by a scatterplot, especially as datasets grow in complexity. Comparison with two baselines -- providing a blank chart and a chart with mismatched data -- shows that the improved performance is due to the content of the charts. Our results are initial evidence that AI systems, like humans, can benefit from visualization.

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Towards interpreting computer vision based on transformation invariant optimization

2021-06-18 · Chen Li, JinZhe Jiang, Xin Zhang, Tonghuan Zhang 외

Interpreting how does deep neural networks (DNNs) make predictions is a vital field in artificial intelligence, which hinders wide applications of DNNs. Visualization of learned representations helps we humans understand…

Data Mining and Visualization to Understand Accident-prone Areas

2021-03-11 · Md Mashfiq Rizvee, Md Amiruzzaman, Md Rajibul Islam

In this study, we present both data mining and information visualization techniques to identify accident-prone areas, most accident-prone time, day, and month. Also, we surveyed among volunteers to understand which visua…

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This paper investigates how working of Convolutional Neural Network (CNN) can be explained through visualization in the context of machine perception of autonomous vehicles. We visualize what type of features are extract…

Autonomous Vehicles Object object-detection Object Detection

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With the growing adoption of machine learning techniques, there is a surge of research interest towards making machine learning systems more transparent and interpretable. Various visualizations have been developed to he…

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Are Gradient-based Saliency Maps Useful in Deep Reinforcement Learning?

2020-12-02 · NeurIPS Workshop ICBINB 2020 12 · Matthias Rosynski, Frank Kirchner, Matias Valdenegro-Toro

Deep Reinforcement Learning (DRL) connects the classic Reinforcement Learning algorithms with Deep Neural Networks. A problem in DRL is that CNNs are black-boxes and it is hard to understand the decision-making process o…

Decision Making Deep Reinforcement Learning image-classification Image Classification+3