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Picasso is an AI-powered dashboard orchestration system that automatically designs dashboards from KPI data by analyzing semantic importance, visual hierarchy, and business relevance. The creator seeks feedback on the project, which is their first using agentic AI workflows.
The paper proposes a permutation-invariant Bayesian optimization method based on Optimal Transport for optimizing offshore wind farm layouts, which reduces computation time by half and yields better layouts compared to vanilla Bayesian optimization.
The paper introduces PaperFit, a vision-in-the-loop agent that iteratively diagnoses and repairs layout defects in LaTeX documents to produce publication-ready PDFs. It also presents a new benchmark, PaperFit-Bench, to evaluate visual typesetting optimization performance.
MM-WebAgent is a hierarchical agentic framework that generates coherent and visually consistent webpages by coordinating AIGC-based element generation through joint optimization of layout and multimodal content. The paper introduces a benchmark and multi-level evaluation protocol, demonstrating improvements over code-generation and agent-based baselines.