Papers Text Simplification
“Text Simplification” 태그가 달린 논문 505편 · 필터 해제
LENS: A Learnable Evaluation Metric for Text Simplification
Training learnable metrics using modern language models has recently emerged as a promising method for the automatic evaluation of machine translation. However, existing human evaluation datasets for text simplification …
Machine TranslationText SimplificationMANTIS at TSAR-2022 Shared Task: Improved Unsupervised Lexical Simplification with Pretrained Encoders
In this paper we present our contribution to the TSAR-2022 Shared Task on Lexical Simplification of the EMNLP 2022 Workshop on Text Simplification, Accessibility, and Readability. Our approach builds on and extends the u…
Language ModelingLanguage ModellingLexical SimplificationNatural Language Inference+3(Psycho-)Linguistic Features Meet Transformer Models for Improved Explainable and Controllable Text Simplification
State-of-the-art text simplification (TS) systems adopt end-to-end neural network models to directly generate the simplified version of the input text, and usually function as a blackbox. Moreover, TS is usually treated …
Text SimplificationPatient-friendly Clinical Notes: Towards a new Text Simplification Dataset
Automatic text simplification can help patients to better understand their own clinical notes. A major hurdle for the development of clinical text simplification methods is the lack of high quality resources. We report o…
Text SimplificationImproving Iterative Text Revision by Learning Where to Edit from Other Revision Tasks
Iterative text revision improves text quality by fixing grammatical errors, rephrasing for better readability or contextual appropriateness, or reorganizing sentence structures throughout a document. Most recent research…
Grammatical Error CorrectionSentenceSentence FusionStyle Transfer+1Cognitive Simplification Operations Improve Text Simplification
Text Simplification (TS) is the task of converting a text into a form that is easier to read while maintaining the meaning of the original text. A sub-task of TS is Cognitive Simplification (CS), converting text to a for…
Inductive BiasText SimplificationNoisy Channel for Automatic Text Simplification
In this paper we present a simple re-ranking method for Automatic Sentence Simplification based on the noisy channel scheme. Instead of directly computing the best simplification given a complex text, the re-ranking meth…
Language ModelingLanguage ModellingRe-RankingSentence+1Is Character Trigram Overlapping Ratio Still the Best Similarity Measure for Aligning Sentences in a Paraphrased Corpus?
Sentence alignment is an essential step in studying the mapping among different language expressions, and the character trigram overlapping ratio was reported to be the most effective similarity measure in aligning sente…
SentenceText SimplificationCEFR-Based Sentence Difficulty Annotation and Assessment
Controllable text simplification is a crucial assistive technique for language learning and teaching. One of the primary factors hindering its advancement is the lack of a corpus annotated with sentence difficulty levels…
SentenceText SimplificationArabic Word-level Readability Visualization for Assisted Text Simplification
This demo paper presents a Google Docs add-on for automatic Arabic word-level readability visualization. The add-on includes a lemmatization component that is connected to a five-level readability lexicon and Arabic Word…
LemmatizationText SimplificationShallow Discourse Parsing for Open Information Extraction and Text Simplification
We present a discourse-aware text simplification (TS) approach that recursively splits and rephrases complex English sentences into a semantic hierarchy of simplified sentences. Using a set of linguistically principled t…
Discourse ParsingOpen Information ExtractionSentenceText SimplificationText Simplification of College Admissions Instructions: A Professionally Simplified and Verified Corpus
Access to higher education is critical for minority populations and emergent bilingual students. However, the language used by higher education institutions to communicate with prospective students is often too complex; …
SentenceText SimplificationUnsupervised Simplification of Legal Texts
The processing of legal texts has been developing as an emerging field in natural language processing (NLP). Legal texts contain unique jargon and complex linguistic attributes in vocabulary, semantics, syntax, and morph…
SentenceText SimplificationPseudo-Labels Are All You Need
Automatically estimating the complexity of texts for readers has a variety of applications, such as recommending texts with an appropriate complexity level to language learners or supporting the evaluation of text simpli…
AllFeature EngineeringPseudo LabelSentence+1Sequence to sequence pretraining for a less-resourced Slovenian language
Large pretrained language models have recently conquered the area of natural language processing. As an alternative to predominant masked language modelling introduced in BERT, the T5 model has introduced a more general …
Language ModelingLanguage ModellingMachine TranslationOpen-Domain Question Answering+4Complex Word Identification in Vietnamese: Towards Vietnamese Text Simplification
Text Simplification has been an extensively researched problem in English, but has not been investigated in Vietnamese. We focus on the Vietnamese-specific Complex Word Identification task, often the first step in Lexica…
Complex Word IdentificationLexical SimplificationText SimplificationVietnamese DatasetsAn Evaluation of Binary Comparative Lexical Complexity Models
Identifying complex words in texts is an important first step in text simplification (TS) systems. In this paper, we investigate the performance of binary comparative Lexical Complexity Prediction (LCP) models applied to…
Lexical Complexity PredictionSentenceText SimplificationUnsupervised Sentence Simplification via Dependency Parsing
Text simplification is the task of rewriting a text so that it is readable and easily understood. In this paper, we propose a simple yet novel unsupervised sentence simplification system that harnesses parsing structures…
Dependency ParsingSentenceSentence EmbeddingsText SimplificationFindings of the The RuATD Shared Task 2022 on Artificial Text Detection in Russian
We present the shared task on artificial text detection in Russian, which is organized as a part of the Dialogue Evaluation initiative, held in 2022. The shared task dataset includes texts from 14 text generators, i.e., …
Binary ClassificationDialogue EvaluationMachine TranslationMulti-class Classification+5Towards Readability-Controlled Machine Translation of COVID-19 Texts
This project investigates the capabilities of Machine Translation models for generating translations at varying levels of readability, focusing on texts related to COVID-19. Whilst it is possible to automatically transla…
Machine TranslationText SimplificationTranslation