11 citations · 12 across the 4 of their papers we have counts for
4 papers
Do Large Multimodal Models Solve Caption Generation for Scientific Figures? Lessons Learned from SciCap Challenge 2023
Ting-Yao E. Hsu, Yi-Li Hsu, Shaurya Rohatgi +8
Since the SciCap datasets launch in 2021, the research community has made significant progress in generating captions for scientific figures in scholarly articles. In 2023, the fir…
Multi-LLM Collaborative Caption Generation in Scientific Documents
Jaeyoung Kim, Jongho Lee, Hong-Jun Choi +8
Scientific figure captioning is a complex task that requires generating contextually appropriate descriptions of visual content. However, existing methods often fall short by utili…
SciCapenter: Supporting Caption Composition for Scientific Figures with Machine-Generated Captions and Ratings
Ting-Yao Hsu, Chieh-Yang Huang, Shih-Hong Huang +5
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 technologi…
GPT-4 as an Effective Zero-Shot Evaluator for Scientific Figure Captions
Ting-Yao Hsu, Chieh-Yang Huang, Ryan Rossi +3
There is growing interest in systems that generate captions for scientific figures. However, assessing these systems output poses a significant challenge. Human evaluation requires…