mlsanityData to 14 Oct 2026

Machine-in-the-Loop Rewriting for Creative Image Captioning

arXiv 2111.04193 ↗First posted 7 Nov 2021cs.CLcited by 11

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Abstract (arXiv)

Machine-in-the-loop writing aims to enable humans to collaborate with models to complete their writing tasks more effectively. Prior work has found that providing humans a machine-written draft or sentence-level continuations has limited success since the generated text tends to deviate from humans' intention. To allow the user to retain control over the content, we train a rewriting model that, when prompted, modifies specified spans of text within the user's original draft to introduce descriptive and figurative elements locally in the text. We evaluate the model on its ability to collaborate with humans on the task of creative image captioning. On a user study through Amazon Mechanical Turk, our model is rated to be more helpful than a baseline infilling language model. In addition, third-party evaluation shows that users write more descriptive and figurative captions when collaborating with our model compared to completing the task alone.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 18 of its 34 references that are in the map. First posted on arXiv 7 Nov 2021.

Builds on

18 of 34 references.

References · 18

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6 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 3; 2023: 3; 2024: 3; 2025: 1; 2026: 1.

11 papers.