36 citations · 82 across the 12 of their papers we have counts for
16 papers
CliniCIRCA: A Modular LLM Framework for Constructing Longitudinal Mental Health Patient Journeys from Raw EHR Narratives
Aiwei Ivy Zhang, Nimra Ishfaq, Mohit Chandra +5
In mental health care, reasoning over patient journeys is a key task for clinicians. Yet these journeys, encompassing a longitudinal progression of biological, psychological, and s…
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…
LLM Prompt Evaluation for Educational Applications
Langdon Holmes, Adam Coscia, Scott Crossley +2
As large language models (LLMs) become increasingly common in educational applications, there is a growing need for evidence-based methods to design and evaluate LLM prompts that p…
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…
DraftMarks: Enhancing Transparency in Human-AI Co-Writing Through Interactive Skeuomorphic Process Traces
Momin N. Siddiqui, Nikki Nasseri, Adam Coscia +2
As generative AI becomes part of everyday writing, questions of transparency and productive human effort are increasingly important. Educators, reviewers, and readers want to under…
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…
Visualizing Intelligent Tutor Interactions for Responsive Pedagogy
Grace Guo, Aishwarya Mudgal Sunil Kumar, Adit Gupta +3
Intelligent tutoring systems leverage AI models of expert learning and student knowledge to deliver personalized tutoring to students. While these intelligent tutors have demonstra…
DeepSee: Multidimensional Visualizations of Seabed Ecosystems
Adam Coscia, Haley M. Sapers, Noah Deutsch +14
Scientists studying deep ocean microbial ecosystems use limited numbers of sediment samples collected from the seafloor to characterize important life-sustaining biogeochemical cyc…
iScore: Visual Analytics for Interpreting How Language Models Automatically Score Summaries
Adam Coscia, Langdon Holmes, Wesley Morris +3
The recent explosion in popularity of large language models (LLMs) has inspired learning engineers to incorporate them into adaptive educational tools that automatically score summ…
KnowledgeVIS: Interpreting Language Models by Comparing Fill-in-the-Blank Prompts
Adam Coscia, Alex Endert
Recent growth in the popularity of large language models has led to their increased usage for summarizing, predicting, and generating text, making it vital to help researchers and…
Preliminary Guidelines For Combining Data Integration and Visual Data Analysis
Adam Coscia, Ashley Suh, Remco Chang +1
Data integration is often performed to consolidate information from multiple disparate data sources during visual data analysis. However, integration operations are usually separat…
Left, Right, and Gender: Exploring Interaction Traces to Mitigate Human Biases
Emily Wall, Arpit Narechania, Adam Coscia +2
Human biases impact the way people analyze data and make decisions. Recent work has shown that some visualization designs can better support cognitive processes and mitigate cognit…
Lumos: Increasing Awareness of Analytic Behavior during Visual Data Analysis
Arpit Narechania, Adam Coscia, Emily Wall +1
Visual data analysis tools provide people with the agency and flexibility to explore data using a variety of interactive functionalities. However, this flexibility may introduce po…
Toward a Bias-Aware Future for Mixed-Initiative Visual Analytics
Adam Coscia, Duen Horng Chau, Alex Endert
Mixed-initiative visual analytics systems incorporate well-established design principles that improve users' abilities to solve problems. As these systems consider whether to take…