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EditLens: Quantifying the extent of AI editing in text (2025)

11 hours ago
  • #computational linguistics
  • #AI detection
  • #text editing
  • The paper introduces EditLens, a method to quantify and detect AI editing in text, distinguishing it from human-written and AI-generated content.
  • Lightweight similarity metrics are proposed to measure the extent of AI editing, validated by human annotators.
  • EditLens, a regression model using these metrics as supervision, achieves state-of-the-art performance in binary (94.7% F1) and ternary (90.4% F1) classification tasks.
  • The research highlights applications in authorship attribution, education, and policy, and includes a case study on AI-edits from Grammarly.
  • The models and dataset will be publicly released to encourage further research.