Papers with text refinement

2 papers
Spotting AI’s Touch: Identifying LLM-Paraphrased Spans in Text (2024.findings-acl)

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Challenge: Existing work focuses on detecting (partially) AI-generated texts, but paraphrasing is commonly employed in various application scenarios for text refinement and diversity.
Approach: They propose a framework for paraphrased text span detection that takes in the full text and assigns each sentence with a score indicating the paraphrasing degree.
Outcome: The proposed framework can detect paraphrased text spans within a text . it takes in the full text and assigns each sentence with a score indicating the paraphrasing degree.
HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs (2026.findings-acl)

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Challenge: High-quality, diverse data are vital for large language models (LLMs) but remain scarce and costly.
Approach: They define the first HSS domain system covering 14 mainstream fields and introduce HSS-Synth.
Outcome: the proposed pipeline outperforms 14 leading baselines on 16 benchmarks.

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