  Crafting effective captions for figures is important. Readers heavily depend
on these captions to grasp the figure's message. However, despite a
well-developed set of AI technologies for figures and captions, these have
rarely been tested for usefulness in aiding caption writing. This paper
introduces SciCapenter, an interactive system that puts together cutting-edge
AI technologies for scientific figure captions to aid caption composition.
SciCapenter generates a variety of captions for each figure in a scholarly
article, providing scores and a comprehensive checklist to assess caption
quality across multiple critical aspects, such as helpfulness, OCR mention, key
takeaways, and visual properties reference. Users can directly edit captions in
SciCapenter, resubmit for revised evaluations, and iteratively refine them. A
user study with Ph.D. students indicates that SciCapenter significantly lowers
the cognitive load of caption writing. Participants' feedback further offers
valuable design insights for future systems aiming to enhance caption writing.
