SOURCE-LINKED INTELLIGENCE
PaperBanana-Interact: Scientific Diagram Refinement with Multi-Turn Human Feedback
Recent efforts have aimed to automate scientific diagram generation from paper content (Lin et al., 2026; Zhu et al., 2026a). However, fully satisfying an author's visual and communicative preferences in a single turn is challenging: in our formative user study (N = 14), all participants requested further revisions after viewing an initial draft, and 86% of them rated the refined diagrams as more satisfactory. Despite the clear demand, the multi-turn workflow remains largely underexplored. To bridge this gap, we present MTPaperBananaBench, a benchmark for multi-turn diagram generation containi
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-31T04:52:32.000Z
First collected: 2026-09-21T07:22:03.933Z. This is not the publication date.