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cs.HC2026

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…

cs.HC2026

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…

cs.HC2026

Drag, Infer, Reproject: Grounding LLMs through Spatial Interaction for Image Clustering

Yang Liu, Xuxin Tang, Jiahao Xu +1

Dimension reduction and semantic interaction support image clustering by making similarity structure visible and manipulable. Existing semantic interaction methods encode users' cl…

cs.HC2026

Context-Aware Explanations for Spatialized Document Layouts

Wei Liu, John Wenskovitch, Chris North +1

Spatialized document layouts are widely used for exploratory analysis of text corpora, but interpreting the spatial organization of documents and the relationships between regions…

cs.HC2026

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…

cs.HC2024

Visualizing Spatial Semantics of Dimensionally Reduced Text Embeddings

Wei Liu, Chris North, Rebecca Faust

Dimension reduction (DR) can transform high-dimensional text embeddings into a 2D visual projection facilitating the exploration of document similarities. However, the projection o…