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 difficulty estimation and simplification

Difficulty Estimation and Simplification of French Text Using LLMs

Jamet, Henri, Shrestha, Yash Raj, Vlachos, Michalis

arXiv.org Artificial Intelligence

We frame both tasks as prediction problems and develop a difficulty classification model using labeled examples, transfer learning, and large language models, demonstrating superior accuracy compared to previous approaches. For simplification, we evaluate the trade-off between simplification quality and meaning preservation, comparing zero-shot and fine-tuned performances of large language models. We show that meaningful text simplifications can be obtained with limited fine-tuning. Our experiments are conducted on French texts, but our methods are language-agnostic and directly applicable to other foreign languages.

  camembert, difficulty estimation and simplification, simplification, (11 more...)
2407.18061
  Country:
  Genre: Research Report > New Finding (0.47)
  Industry: Education (1.00)
  Technology:

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