Visualization Method

Data visualization methods are rapidly evolving to address the challenges of interpreting increasingly complex datasets, particularly in machine learning and computer vision. Current research focuses on developing techniques that improve model explainability and trustworthiness, often leveraging large language models and deep learning approaches to generate insightful visualizations from high-dimensional data, including embedding spaces and optimization trajectories. These advancements are crucial for enhancing understanding of model behavior, identifying biases, and ultimately improving the reliability and interpretability of AI systems across diverse scientific and practical applications.