Text Simplification
It is the task of modifying the content and structure of a text in order to make it easier to read and understand, while retaining its main idea and approximating its original meaning. When simplifying sentences, different rewriting transformations are performed, which range from replacing complex words or phrases for simpler synonyms, to changing the syntactic structure of the sentence. Modern SS approaches are data-driven; that is, they attempt to learn these transformations using parallel corpora of aligned original-simplified sentences. This results in general simplification models that could be used for any specific type of audience, depending on the data used during training.
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Data Science
Foundations of Large Language Models Course
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Corpora for Simplification
Data-Driven Approaches to Sentence Simplification
Examples of Prompt Templates for Text Simplification
Simplifying Prompt Text for Efficiency
Sequence-to-Sequence Models for Text Simplification
A system is designed to modify text to make it easier to read while preserving the original meaning. Given the original sentence below, which of the following outputs represents the most successful modification according to these goals?
Original: "The legislative body's recent enactment of the statute, which was predicated on extensive empirical analysis, is anticipated to have a profound and multifaceted impact on the nation's socioeconomic fabric."
Evaluating Text Simplification Models
Data Requirements for a Targeted Text Simplification System