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cs.HC2026
Lexara-RF: Reference-Free Metrics for Evaluating Conversational Visual Analytics Agents
Srishti Palani, Vidya Setlur
Conversational visual analytics (CVA) agents powered by large language models generate visualizations and natural-language explanations from open-ended queries. Evaluating these mu…
cs.HC2026
Lexara: A User-Centered Toolkit for Evaluating Large Language Models for Conversational Visual Analytics
Srishti Palani, Vidya Setlur
Large Language Models (LLMs) are transforming Conversational Visual Analytics (CVA) by enabling data analysis through natural language. However, evaluating LLMs for CVA remains a c…
cs.HC2026
"I Need to Find That One Chart": How Data Workers Navigate, Make Sense of, and Communicate Analytical Conversations
Ken Gu, Srishti Palani, Vidya Setlur
Conversational interfaces are increasingly used for data analysis, enabling data workers to express complex analytical intents in natural language. Yet, these interactions unfold a…