AI RESEARCH
Lexara: A User-Centered Toolkit for Evaluating Large Language Models for Conversational Visual Analytics
arXiv CS.AI
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ArXi:2603.05832v1 Announce Type: cross Large Language Models (LLMs) are transforming Conversational Visual Analytics (CVA) by enabling data analysis through natural language. However, evaluating LLMs for CVA remains a challenge: requiring programming expertise, overlooking real-world complexity, and lacking interpretable metrics for multi-format (visualizations and text) outputs. Through interviews with 22 CVA developers and 16 end-users, we identified use cases, evaluation criteria and workflows.