TY - GEN
T1 - Understanding How Paper Writers Use AI-Generated Captions in Figure Caption Writing
AU - Ng, Ho Yin
AU - Hsu, Ting Yao
AU - Min, Jiyoo
AU - Kim, Sungchul
AU - Rossi, Ryan A.
AU - Yu, Tong
AU - Jung, Hyunggu
AU - Huang, Ting Hao ‘Kenneth’
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - Figures and their captions play a key role in scientific publications. However, despite their importance, many captions in published papers are poorly crafted, largely due to a lack of attention by paper authors. While prior AI research has explored caption generation, it has mainly focused on reader-centered use cases, where users evaluate generated captions rather than actively integrating them into their writing. This paper addresses this gap by investigating how paper authors incorporate AI-generated captions into their writing process through a user study involving 18 participants. Each participant rewrote captions for two figures from their own recently published work, using captions generated by state-of-the-art AI models as a resource. By analyzing video recordings of the writing process through interaction analysis, we observed that participants often began by copying and refining AI-generated captions. Paper writers favored longer, detail-rich captions that integrated textual and visual elements but found current AI models less effective for complex figures. These findings highlight the nuanced and diverse nature of figure caption composition, revealing design opportunities for AI systems to better support the challenges of academic writing.
AB - Figures and their captions play a key role in scientific publications. However, despite their importance, many captions in published papers are poorly crafted, largely due to a lack of attention by paper authors. While prior AI research has explored caption generation, it has mainly focused on reader-centered use cases, where users evaluate generated captions rather than actively integrating them into their writing. This paper addresses this gap by investigating how paper authors incorporate AI-generated captions into their writing process through a user study involving 18 participants. Each participant rewrote captions for two figures from their own recently published work, using captions generated by state-of-the-art AI models as a resource. By analyzing video recordings of the writing process through interaction analysis, we observed that participants often began by copying and refining AI-generated captions. Paper writers favored longer, detail-rich captions that integrated textual and visual elements but found current AI models less effective for complex figures. These findings highlight the nuanced and diverse nature of figure caption composition, revealing design opportunities for AI systems to better support the challenges of academic writing.
UR - https://www.scopus.com/pages/publications/105010816242
UR - https://www.scopus.com/pages/publications/105010816242#tab=citedBy
U2 - 10.1007/978-981-96-8912-5_8
DO - 10.1007/978-981-96-8912-5_8
M3 - Conference contribution
AN - SCOPUS:105010816242
SN - 9789819689118
T3 - Communications in Computer and Information Science
SP - 173
EP - 192
BT - AI for Research and Scalable, Efficient Systems - Second International Workshop, AI4Research 2025, and First International Workshop, SEAS 2025, Held in Conjunction with AAAI 2025, Proceedings
A2 - Wang, Qingyun
A2 - Yin, Wenpeng
A2 - Aich, Abhishek
A2 - Suh, Yumin
A2 - Peng, Kuan-Chuan
PB - Springer Science and Business Media Deutschland GmbH
T2 - 2nd AI4Research Workshop: Towards a Knowledge-Grounded Scientific Research Lifecycle, AI4Research 2025 and 1st Workshop on Scalable and Efficient Artificial Intelligence Systems, SEAS 2025, held in conjunction with the 39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025
Y2 - 25 February 2025 through 4 March 2025
ER -