PaperBanana-Interact is a multi-agent system for refining scientific diagrams through iterative human feedback, accompanied by MTPaperBananaBench, a benchmark of 292 annotated images with 3,518 user requirements, and a user simulator for scalable evaluation. An internal critique-and-refine loop addresses quality degradation and feature forgetting across refinement turns, achieving substantial gains over baseline approaches.
