A structured multi stage interface generation framework that decomposes the task into visualization design representation, generation of multiple interface candidates, constraint-aware critique, and self-refinement is proposed, demonstrating a practical path toward more reliable language-driven interactive visualizatio...
This work introduces VisEditBench, a benchmark of 1,395 human-annotated visualization code-editing tasks grounded in realistic visualization workflows and failure cases, and proposes VisEditAgent, a render-grounded editing framework that iteratively generates, executes, validates, and refines candidate edits.
DSAgentBench is introduced, the first benchmark to evaluate whether agents can automate full data-science workflows inside real computer environments, and reveals a substantial capability gap between current agentic systems and real data-science workflows.
Mizanur Rahman, Mohammed Saidul Islam, Ridwan Mahbub et al.· 0 citations
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