Papers Text Simplification
“Text Simplification” 태그가 달린 논문 505편 · 필터 해제
German Text Simplification: Finetuning Large Language Models with Semi-Synthetic Data
This study pioneers the use of synthetically generated data for training generative models in document-level text simplification of German texts. We demonstrate the effectiveness of our approach with real-world online te…
Text SimplificationMedTSS: transforming abstractive summarization of scientific articles with linguistic analysis and concept reinforcement
This research addresses the limitations of pretrained models (PTMs) in generating accurate and comprehensive abstractive summaries for scientific articles, with a specific focus on the challenges posed by medical researc…
Abstractive Text SummarizationArticlesHallucinationText SimplificationInfoLossQA: Characterizing and Recovering Information Loss in Text Simplification
Text simplification aims to make technical texts more accessible to laypeople but often results in deletion of information and vagueness. This work proposes InfoLossQA, a framework to characterize and recover simplificat…
Natural Language InferenceText SimplificationHealth Text Simplification: An Annotated Corpus for Digestive Cancer Education and Novel Strategies for Reinforcement Learning
Objective: The reading level of health educational materials significantly influences the understandability and accessibility of the information, particularly for minoritized populations. Many patient educational resourc…
Domain AdaptationLanguage ModellingLarge Language Modelreinforcement-learning+3Data and Approaches for German Text simplification -- towards an Accessibility-enhanced Communication
This paper examines the current state-of-the-art of German text simplification, focusing on parallel and monolingual German corpora. It reviews neural language models for simplifying German texts and assesses their suita…
Text SimplificationExploring Automatic Text Simplification of German Narrative Documents
In this paper, we apply transformer-based Natural Language Generation (NLG) techniques to the problem of text simplification. Currently, there are only a few German datasets available for text simplification, even fewer …
Text GenerationText SimplificationA Novel Dataset for Financial Education Text Simplification in Spanish
Text simplification, crucial in natural language processing, aims to make texts more comprehensible, particularly for specific groups like visually impaired Spanish speakers, a less-represented language in this field. In…
Data AugmentationSentenceText SimplificationDo Text Simplification Systems Preserve Meaning? A Human Evaluation via Reading Comprehension
Automatic text simplification (TS) aims to automate the process of rewriting text to make it easier for people to read. A pre-requisite for TS to be useful is that it should convey information that is consistent with the…
Question AnsweringReading ComprehensionText SimplificationAscle: A Python Natural Language Processing Toolkit for Medical Text Generation
This study introduces Ascle, a pioneering natural language processing (NLP) toolkit designed for medical text generation. Ascle is tailored for biomedical researchers and healthcare professionals with an easy-to-use, all…
Machine TranslationQuestion AnsweringSentence segmentationText Generation+3BLESS: Benchmarking Large Language Models on Sentence Simplification
We present BLESS, a comprehensive performance benchmark of the most recent state-of-the-art large language models (LLMs) on the task of text simplification (TS). We examine how well off-the-shelf LLMs can solve this chal…
BenchmarkingDiversitySentenceText SimplificationEvaluation Metrics in the Era of GPT-4: Reliably Evaluating Large Language Models on Sequence to Sequence Tasks
Large Language Models (LLMs) evaluation is a patchy and inconsistent landscape, and it is becoming clear that the quality of automatic evaluation metrics is not keeping up with the pace of development of generative model…
Grammatical Error CorrectionText SimplificationMedical Text Simplification: Optimizing for Readability with Unlikelihood Training and Reranked Beam Search Decoding
Text simplification has emerged as an increasingly useful application of AI for bridging the communication gap in specialized fields such as medicine, where the lexicon is often dominated by technical jargon and complex …
DiversityText SimplificationBibRank: Automatic Keyphrase Extraction Platform Using~Metadata
Automatic Keyphrase Extraction involves identifying essential phrases in a document. These keyphrases are crucial in various tasks such as document classification, clustering, recommendation, indexing, searching, summari…
ClusteringDocument ClassificationKeyphrase ExtractionText SimplificationAutomatic and Human-AI Interactive Text Generation
In this tutorial, we focus on text-to-text generation, a class of natural language generation (NLG) tasks, that takes a piece of text as input and then generates a revision that is improved according to some specific cri…
Paraphrase GenerationStyle TransferText GenerationText Simplification+1LC-Score: Reference-less estimation of Text Comprehension Difficulty
Being able to read and understand written text is critical in a digital era. However, studies shows that a large fraction of the population experiences comprehension issues. In this context, further initiatives in access…
Reading ComprehensionText SimplificationIs it Possible to Modify Text to a Target Readability Level? An Initial Investigation Using Zero-Shot Large Language Models
Text simplification is a common task where the text is adapted to make it easier to understand. Similarly, text elaboration can make a passage more sophisticated, offering a method to control the complexity of reading co…
Language ModellingReading ComprehensionText SimplificationInvestigating Large Language Models and Control Mechanisms to Improve Text Readability of Biomedical Abstracts
Biomedical literature often uses complex language and inaccessible professional terminologies. That is why simplification plays an important role in improving public health literacy. Applying Natural Language Processing …
DecoderText SimplificationRedPenNet for Grammatical Error Correction: Outputs to Tokens, Attentions to Spans
The text editing tasks, including sentence fusion, sentence splitting and rephrasing, text simplification, and Grammatical Error Correction (GEC), share a common trait of dealing with highly similar input and output sequ…
Grammatical Error CorrectionMachine Translationnamed-entity-recognitionNamed Entity Recognition+7ARTIST: ARTificial Intelligence for Simplified Text
Complex text is a major barrier for many citizens when accessing public information and knowledge. While often done manually, Text Simplification is a key Natural Language Processing task that aims for reducing the lingu…
Text SimplificationA User-Centered Evaluation of Spanish Text Simplification
We present an evaluation of text simplification (TS) in Spanish for a production system, by means of two corpora focused in both complex-sentence and complex-word identification. We compare the most prevalent Spanish-spe…
Complex Word IdentificationSentenceText Simplification