PaperBanana: AI Automating Academic Illustration - Showcase Project

PaperBanana is an AI-powered agentic framework designed to automate academic illustration. We transform raw scientific content into publication-quality diagrams and plots, lifting the design bottleneck in your research workflow. Despite rapid advances in AI, generating accurate, venue-ready figures remains a labor-intensive task for researchers. PaperBanana solves this by orchestrating a team of five specialized AI agents (Retriever, Planner, Stylist, Visualizer, and Critic) to handle the heavy lifting. Key Features: Multi-Agent Workflow: An iterative, self-critiquing pipeline ensures your diagrams meet the strict aesthetic standards of top-tier venues (NeurIPS, ICML, ICLR). Accurate Statistical Plots: We generate executable Python Matplotlib code for data visualization, ensuring 100% numerical accuracy and zero AI hallucinations. Methodology Diagrams: Easily visualize complex algorithms, neural network architectures, and multi-agent system pipelines from simple text descriptions. Aesthetic Enhancement: Upload a quick hand-drawn sketch or an existing basic diagram, and our AI will elevate it into a polished, professional graphic without altering the underlying logic. Stop spending hours wrestling with design tools. Let PaperBanana turn your scientific concepts into academic masterpieces.