T5 language models for text simplification
نویسندگان
چکیده
منابع مشابه
Exploring Neural Text Simplification Models
We present the first attempt at using sequence to sequence neural networks to model text simplification (TS). Unlike the previously proposed automated TS systems, our neural text simplification (NTS) systems are able to simultaneously perform lexical simplification and content reduction. An extensive human evaluation of the output has shown that NTS systems achieve almost perfect grammaticality...
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In this paper we examine language modeling for text simplification. Unlike some text-to-text translation tasks, text simplification is a monolingual translation task allowing for text in both the input and output domain to be used for training the language model. We explore the relationship between normal English and simplified English and compare language models trained on varying amounts of t...
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Simplified texts are commonly used by teachers and students in bilingual education and other language-learning contexts. These texts are usually manually adapted, and teachers say this is a timeconsuming and sometimes challenging task. Our goal is the development of tools to aid teachers by automatically proposing ways to simplify texts. As a first step, this paper presents a detailed analysis ...
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In this paper we discuss particular choices we made during the development of a rule-based syntactic text simplification system. Such choices concern 1) how to deal with adverbial phrases in order to simplify sentences, and 2) the order in which to apply our set of simplification rules. Adverbial phrases have not been considered by previous work on text simplification, but have a considerable i...
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We describe a readability assessment approach to support the process of text simplification for poor literacy readers. Given an input text, the goal is to predict its readability level, which corresponds to the literacy level that is expected from the target reader: rudimentary, basic or advanced. We complement features traditionally used for readability assessment with a number of new features...
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ژورنال
عنوان ژورنال: ??????????? ???????? ? ???????
سال: 2023
ISSN: ['2311-2735', '0236-235X']
DOI: https://doi.org/10.15827/0236-235x.142.228-236