Publications (13)
Embodied Natural Language Interaction (NLI): Speech Input Patterns in Immersive Analytics
Hyemi Song, Matthew Johnson, Kirsten Whitley +2
Embodiment shapes how users verbally express intent when interacting with data through speech interfaces in immersive analytics. Despite growing interest in Natural Language Intera…
Agentic Reasoning and Refinement through Semantic Interaction
Xuxin Tang, Rehema Abulikemu, Eric Krokos +3
Sensemaking report writing often requires multiple refinements in the iterative process. While Large Language Models (LLMs) have shown promise in generating initial reports based o…
Investigating Seamless Transitions Between Immersive Computational Notebooks and Embodied Data Interactions
Sungwon In, Eric Krokos, Kirsten Whitley +2
A growing interest in Immersive Analytics (IA) has led to the extension of computational notebooks (e.g., Jupyter Notebook) into an immersive environment to enhance analytical work…
Semantic Interaction for Narrative Map Sensemaking: An Insight-based Evaluation
Brian Felipe Keith-Norambuena, Fausto German, Eric Krokos +2
Semantic interaction (SI) enables analysts to incorporate their cognitive processes into AI models through direct manipulation of visualizations. While SI frameworks for narrative…
Scalable Semantic Steering of Embedding Projections
Wei Liu, Eric Krokos, Kirsten Whitley +2
Low-dimensional projections support interactive visual analysis of high-dimensional data embeddings, but their structure often does not align with analyst-defined semantic relation…
Towards an Embodied Composition Framework for Organizing Immersive Computational Notebooks
Sungwon In, Eric Krokos, Kirsten Whitley +2
As immersive technologies evolve, immersive computational notebooks offer new opportunities for interacting with code, data, and outputs. However, scaling these environments remain…
Explainable AI Components for Narrative Map Extraction
Brian Keith, Fausto German, Eric Krokos +2
As narrative extraction systems grow in complexity, establishing user trust through interpretable and explainable outputs becomes increasingly critical. This paper presents an eval…
Steering LLM Summarization with Visual Workspaces for Sensemaking
Xuxin Tang, Eric Krokos, Can Liu +4
Large Language Models (LLMs) have been widely applied in summarization due to their speedy and high-quality text generation. Summarization for sensemaking involves information comp…
Semantic Prompting: Agentic Incremental Narrative Refinement through Spatial Semantic Interaction
Xuxin Tang, Ibrahim Tahmid, Eric Krokos +3
Interactive spatial layouts empower users to synthesize information and organize findings for sensemaking. While Large Language Models (LLMs) can automate narrative generation from…
LLM-Augmented Semantic Steering of Text Embedding Projection Spaces
Wei Liu, Eric Krokos, Kirsten Whitley +2
Low-dimensional projections of text embeddings support visual analysis of document collections, but their spatial organization may not reflect the relationships an analyst intends…
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…
Spatial Visual Analytics for Multi-Document Summary Verification
Jiahao Xu, Wei Liu, Yang Liu +5
Large language models increasingly generate summaries from collections of documents to support sensemaking and reporting, but verifying whether summary statements are grounded in s…
Exploring Organizational Strategies in Immersive Computational Notebooks
Sungwon In, Ayush Roy, Eric Krokos +3
Computational notebooks, which integrate code, documentation, tags, and visualizations into a single document, have become increasingly popular for data analysis tasks. With the ad…