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Data clustering is a common unsupervised learning method frequently used in exploratory data analysis. However, identifying relevant structures in unlabeled, high-dimensional data is nontrivial, requiring iterative experimentation with…
Large language models (LLMs) have achieved remarkable performance across a wide range of natural language tasks. Understanding how LLMs internally represent knowledge remains a significant challenge. Despite Sparse Autoencoders (SAEs) have…
Visual Graph Query Interfaces (VQIs) empower non-programmers to query graph data by constructing visual queries intuitively. Devising efficient technologies in Graph Query Engines (GQEs) for interactive search and exploration has also been…
Human reasoning in visual analytics of data networks relies mainly on the quality of visual perception and the capability of interactively exploring the data from different facets. Visual quality strongly depends on networks' size and…
Causal inference from observational data is a subject of active research and development in statistics and computer science. Many toolkits have been developed for this purpose that depends on statistical software. However, these toolkits do…
Today's data analytics frameworks are compute-centric, with analytics execution almost entirely dependent on the pre-determined physical structure of the high-level computation. Relegating intermediate data to a second class entity in this…
Hillview is a distributed spreadsheet for browsing very large datasets that cannot be handled by a single machine. As a spreadsheet, Hillview provides a high degree of interactivity that permits data analysts to explore information quickly…
This paper describes a system to support the visual exploration of Open Data. During his/her interactive experience with the graphics, the user can easily store the current complete state of the visualization application (called a…
Designers rely on visual search to explore and develop ideas in early design stages. However, designers can struggle to identify suitable text queries to initiate a search or to discover images for similarity-based search that can…
Current video analytics approaches face a fundamental trade-off between flexibility and efficiency. End-to-end Vision Language Models (VLMs) often struggle with long-context processing and incur high computational costs, while…
Through a natural language interface (NLI) for exploratory visual analysis, users can directly "ask" analytical questions about the given tabular data. This process greatly improves user experience and lowers the technical barriers of data…
In this paper we show how advanced visualization tools can help the researcher in investigating and extracting information from data. The focus is on VisIVO, a novel open source graphics application, which blends high performance…
This paper introduces a novel visual analytics approach, DCPViz, to enable climate scientists to explore massive climate data interactively without requiring the upfront movement of massive data. Thus, climate scientists are afforded more…
Data exploration and visualization systems are of great importance in the Big Data era. Exploring and visualizing very large datasets has become a major research challenge, of which scalability is a vital requirement. In this survey, we…
Most tabular data visualization techniques focus on overviews, yet many practical analysis tasks are concerned with investigating individual items of interest. At the same time, relating an item to the rest of a potentially large table is…
In the present work we have selected a collection of statistical and mathematical tools useful for the exploration of multivariate data and we present them in a form that is meant to be particularly accessible to a classically trained…
Multimodal interfaces that combine direct manipulation and natural language have shown great promise for data visualization. Such multimodal interfaces allow people to stay in the flow of their visual exploration by leveraging the strengths…
In visual exploration and analysis of data, determining how to select and transform the data for visualization is a challenge for data-unfamiliar or inexperienced users. Our main hypothesis is that for many data sets and common analysis…
The increasing complexity and scale of scientific datasets demand advanced tools for efficient discovery and exploration. Traditional search systems often fall short in addressing the multidimensional nature of data and their intricate…
Due to the rapid growth of the World Wide Web, resource discovery becomes an increasing problem. As an answer to the demand for information management, a third generation of World-Wide Web tools will evolve: information gathering and…