Papers with text manipulation

3 papers
A Ship of Theseus: Curious Cases of Paraphrasing in LLM-Generated Texts (2024.acl-long)

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Challenge: Using a computational approach, we discover that diminishing performance in text classification models is closely associated with the extent of deviation from the original author’s style.
Approach: They propose to use large language models to determine whether a text retains original authorship when it undergoes numerous paraphrasing iterations.
Outcome: The results suggest that authorship should be task-dependent .
TNT: Text Normalization based Pre-training of Transformers for Content Moderation (2020.emnlp-main)

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Challenge: Language model pre-training (self-supervised or unsupervised learning) has been widely used in a multitude of language processing tasks such as named entity recognition, sentiment analysis, question answering and content moderation.
Approach: They propose a new language pre-training model TNT for content moderation that uses a combination of masking strategy and text normalization to learn from text.
Outcome: The proposed model outperforms baselines on hate speech classification task and is a potential approach to misspelling correction.
NewsCLIPpings: Automatic Generation of Out-of-Context Multimodal Media (2021.emnlp-main)

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Challenge: a threat scenario where an image is used out of context to support a narrative is proposed.
Approach: They propose a dataset where both image and text are unmanipulated but mismatched . they benchmark several state-of-the-art multimodal models on their dataset .
Outcome: The proposed dataset shows that machine-driven image repurposing is now a realistic threat . it provides samples that represent challenging instances of mismatch between text and image .

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