6 citations · 16 across the 12 of their papers we have counts for
14 papers
Targeted and Traceable Investigation of Multi-Agent LLM Dialogue via Semantic Bundling of Knowledge Graphs
Zeyu Hua, Adam Coscia, Alex Endert
Multi-agent LLM systems today are increasingly automated, logging LLM-LLM interactions as conversational transcripts. Yet analyzing such dialogue for insights remains challenging,…
Calibrating Trustworthiness: Co-Designing Metrics and Visualizations for Evaluating LLMs in Education
Adam Coscia, Sujata Duwal, Langdon Holmes +2
LLMs are reshaping educational technology, yet evaluating their responses for pedagogical alignment remains underexplored, relying heavily on the expertise of learning engineers bu…
Semantic Bundling: Interactive Node and Edge Bundling to Simplify Knowledge Graphs using Large Language Models
Adam Coscia, Zeyu Hua, Eric Krokos +2
We present Semantic Bundling, a visual analytics technique for making sense of text documents represented as knowledge graphs (KGs). Representing a document corpus as a KG makes re…
Guidelines for Designing AI Technologies to Support Adult Learning
Jennifer M. Reddig, Glen R. Smith, Sanaz Ahmadzadeh Siyahrood +16
AI-powered educational technologies have demonstrated measurable benefits for learners, but their design and evaluation have largely centered on K-12 contexts. As a result, many AI…
Exploropleth: exploratory analysis of data binning methods in choropleth maps
Arpit Narechania, Alex Endert, Clio Andris
When creating choropleth maps, mapmakers often bin (i.e., group, classify) quantitative data values into groups to help show that certain areas fall within a similar range of value…
VisPile: A Visual Analytics System for Analyzing Multiple Text Documents With Large Language Models and Knowledge Graphs
Adam Coscia, Alex Endert
Intelligence analysts perform sensemaking over collections of documents using various visual and analytic techniques to gain insights from large amounts of text. As data scales gro…
OnGoal: Tracking and Visualizing Conversational Goals in Multi-Turn Dialogue with Large Language Models
Adam Coscia, Shunan Guo, Eunyee Koh +1
As multi-turn dialogues with large language models (LLMs) grow longer and more complex, how can users better evaluate and review progress on their conversational goals? We present…
Agentic Enterprise: AI-Centric User to User-Centric AI
Arpit Narechania, Alex Endert, Atanu R Sinha
After a very long winter, the Artificial Intelligence (AI) spring is here. Or, so it seems over the last three years. AI has the potential to impact many areas of human life - pers…
Utilizing Provenance as an Attribute for Visual Data Analysis: A Design Probe with ProvenanceLens
Arpit Narechania, Shunan Guo, Eunyee Koh +2
Analytic provenance can be visually encoded to help users track their ongoing analysis trajectories, recall past interactions, and inform new analytic directions. Despite its signi…
Cartographers in Cubicles: How Training and Preferences of Mapmakers Interplay with Structures and Norms in Not-for-Profit Organizations
Arpit Narechania, Alex Endert, Clio Andris
Choropleth maps are a common and effective way to visualize geographic thematic data. Although cartographers have established many principles about map design, data binning and col…
Guidance Source Matters: How Guidance from AI, Expert, or a Group of Analysts Impacts Visual Data Preparation and Analysis
Arpit Narechania, Alex Endert, Atanu R Sinha
The progress in generative AI has fueled AI-powered tools like co-pilots and assistants to provision better guidance, particularly during data analysis. However, research on guidan…
Ego vs. Exo and Active vs. Passive: Investigating the Individual and Combined Effects of Viewpoint and Navigation on Spatial Immersion and Understanding in Immersive Storytelling
Tao Lu, Qian Zhu, Tiffany Ma +4
Visual storytelling combines visuals and narratives to communicate important insights. While web-based visual storytelling is well-established, leveraging the next generation of di…
Generating Analytic Specifications for Data Visualization from Natural Language Queries using Large Language Models
Subham Sah, Rishab Mitra, Arpit Narechania +3
Recently, large language models (LLMs) have shown great promise in translating natural language (NL) queries into visualizations, but their "black-box" nature often limits explaina…
ProvenanceWidgets: A Library of UI Control Elements to Track and Dynamically Overlay Analytic Provenance
Arpit Narechania, Kaustubh Odak, Mennatallah El-Assady +1
We present ProvenanceWidgets, a Javascript library of UI control elements such as radio buttons, checkboxes, and dropdowns to track and dynamically overlay a user's analytic proven…