mlsanityData to 7 Oct 2026

Paraphrase Acquisition from Image Captions

arXiv 2301.11030 ↗First posted 26 Jan 2023cs.CLcited by 1

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Abstract (arXiv)

We propose to use image captions from the Web as a previously underutilized resource for paraphrases (i.e., texts with the same "message") and to create and analyze a corresponding dataset. When an image is reused on the Web, an original caption is often assigned. We hypothesize that different captions for the same image naturally form a set of mutual paraphrases. To demonstrate the suitability of this idea, we analyze captions in the English Wikipedia, where editors frequently relabel the same image for different articles. The paper introduces the underlying mining technology, the resulting Wikipedia-IPC dataset, and compares known paraphrase corpora with respect to their syntactic and semantic paraphrase similarity to our new resource. In this context, we introduce characteristic maps along the two similarity dimensions to identify the style of paraphrases coming from different sources. An annotation study demonstrates the high reliability of the algorithmically determined characteristic maps.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 13 of its 44 references that are in the map. First posted on arXiv 26 Jan 2023.

Builds on

13 of 44 references.

References · 13

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  4. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  5. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,462
  6. 2019PAWS: Paraphrase Adversaries from Word Scramblingcited by 395
  7. 2017A Continuously Growing Dataset of Sentential Paraphrasescited by 72
  8. 2016Neural Paraphrase Generation with Stacked Residual LSTM Networkscited by 52
  9. 2017ParaNMT-50M: Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translationscited by 44
  10. 2022How Large Language Models are Transforming Machine-Paraphrased Plagiarismcited by 38
  11. 2018Open Subtitles Paraphrase Corpus for Six Languagescited by 24
  12. 2020Unsupervised Paraphrasing with Pretrained Language Modelscited by 15
1 more
  1. 2015Segment-Phrase Table for Semantic Segmentation, Visual Entailment and Paraphrasingcited by 1

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