With the surge of data-driven analysis techniques, there is a rising demand for enhancing
the exploration of large high-dimensional data by enabling interactions for the joint analysis …

Co-adaptive guidance aims to enable efficient human-machine collaboration in visual
analytics, as proposed by multiple theoretical frameworks. This paper bridges the gap …

Large language models (LLMs) have gained popularity in various fields for their exceptional
capability of generating human-like text. Their potential misuse has raised social concerns …

Visual analytics supports data analysis tasks within complex domain problems. However,
due to the richness of data types, visual designs, and interaction designs, users need to …

Unexploded Ordnance (UXO) detection, the identification of remnant active bombs buried
underground from archival aerial images, implies a complex workflow involving decision …

Guidance in visual analytics aims to support users in accomplishing their analytical goals
and generating insights. Different approaches for guidance are widely adopted in many …

Computational models, such as simulations, are central to a wide range of fields in science
and industry. Those models take input parameters and produce some output. To fully exploit …

Guidance can support users during the exploration and analysis of complex data. Previous
research focused on characterizing the theoretical aspects of guidance in visual analytics …

Visual data analysis helps to understand different types of phenomena by allowing experts
to explore for relationships, patterns, outliers, unexpected changes, and more. Experts need …

Active learning (AL) systems have become increasingly popular for various applications in
machine learning (ML), including medical imaging, environmental monitoring, and …