SOURCE-LINKED INTELLIGENCE
Lexara-RF: Reference-Free Metrics for Evaluating Conversational Visual Analytics Agents
Conversational visual analytics (CVA) agents powered by large language models generate visualizations and natural-language explanations from open-ended queries. Evaluating these multimodal outputs is challenging: curated reference benchmarks are costly to author, cannot comprehensively capture the space of valid responses, and are unavailable in production. Building on the Lexara evaluation framework, we introduce Lexara-RF, a reference-free set of metrics that scores CVA outputs using only the prompt, data, and model response. We reformulate evaluation as verification: 13 metrics operationali
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-15T21:02:24.000Z
First collected: 2026-09-20T08:20:57.646Z. This is not the publication date.