Papers Text Simplification
“Text Simplification” 태그가 달린 논문 505편 · 필터 해제
Resource for Error Analysis in Text Simplification: New Taxonomy and Test Collection
The general public often encounters complex texts but does not have the time or expertise to fully understand them, leading to the spread of misinformation. Automatic Text Simplification (ATS) helps make information more…
MisinformationText GenerationText SimplificationA Structured Literature Review on Traditional Approaches in Current Natural Language Processing
The continued rise of neural networks and large language models in the more recent past has altered the natural language processing landscape, enabling new approaches towards typical language tasks and achieving mainstre…
Relation ExtractionSurveyText SimplificationText SummarizationLLM-based Text Simplification and its Effect on User Comprehension and Cognitive Load
Information on the web, such as scientific publications and Wikipedia, often surpasses users' reading level. To help address this, we used a self-refinement approach to develop a LLM capability for minimally lossy text s…
ArticlesMultiple-choicePhilosophyText SimplificationSimplifyMyText: An LLM-Based System for Inclusive Plain Language Text Simplification
Text simplification is essential for making complex content accessible to diverse audiences who face comprehension challenges. Yet, the limited availability of simplified materials creates significant barriers to persona…
Text SimplificationEvaluation Under Imperfect Benchmarks and Ratings: A Case Study in Text Simplification
Despite the successes of language models, their evaluation remains a daunting challenge for new and existing tasks. We consider the task of text simplification, commonly used to improve information accessibility, where e…
Text SimplificationAutomatic Input Rewriting Improves Translation with Large Language Models
Can we improve machine translation (MT) with LLMs by rewriting their inputs automatically? Users commonly rely on the intuition that well-written text is easier to translate when using off-the-shelf MT systems. LLMs can …
Machine TranslationText SimplificationTranslationAligning Sentence Simplification with ESL Learner's Proficiency for Language Acquisition
Text simplification is crucial for improving accessibility and comprehension for English as a Second Language (ESL) learners. This study goes a step further and aims to facilitate ESL learners' language acquisition by si…
DiversityLanguage AcquisitionLanguage ModelingLanguage Modelling+3Eye Tracking Based Cognitive Evaluation of Automatic Readability Assessment Measures
Automated text readability prediction is widely used in many real-world scenarios. Over the past century, such measures have primarily been developed and evaluated on reading comprehension outcomes and on human annotatio…
AllReading ComprehensionText SimplificationImproving Estonian Text Simplification through Pretrained Language Models and Custom Datasets
This study introduces an approach to Estonian text simplification using two model architectures: a neural machine translation model and a fine-tuned large language model (LLaMA). Given the limited resources for Estonian,…
Language ModelingLanguage ModellingLarge Language ModelMachine Translation+2Evaluating GenAI for Simplifying Texts for Education: Improving Accuracy and Consistency for Enhanced Readability
Generative artificial intelligence (GenAI) holds great promise as a tool to support personalized learning. Teachers need tools to efficiently and effectively enhance content readability of educational texts so that they …
Semantic SimilaritySemantic Textual SimilarityText SimplificationDisSim-FinBERT: Text Simplification for Core Message Extraction in Complex Financial Texts
This study proposes DisSim-FinBERT, a novel framework that integrates Discourse Simplification (DisSim) with Aspect-Based Sentiment Analysis (ABSA) to enhance sentiment prediction in complex financial texts. By simplifyi…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Sentiment AnalysisText SimplificationProgressive Document-level Text Simplification via Large Language Models
Research on text simplification has primarily focused on lexical and sentence-level changes. Long document-level simplification (DS) is still relatively unexplored. Large Language Models (LLMs), like ChatGPT, have excell…
Document SummarizationSentenceText SimplificationM-Ped: Multi-Prompt Ensemble Decoding for Large Language Models
With the widespread application of Large Language Models (LLMs) in the field of Natural Language Processing (NLP), enhancing their performance has become a research hotspot. This paper presents a novel multi-prompt ensem…
Code GenerationMachine TranslationText SimplificationSimple is not Enough: Document-level Text Simplification using Readability and Coherence
In this paper, we present the SimDoc system, a simplification model considering simplicity, readability, and discourse aspects, such as coherence. In the past decade, the progress of the Text Simplification (TS) field ha…
SentenceText SimplificationSiTSE: Sinhala Text Simplification Dataset and Evaluation
Text Simplification is a task that has been minimally explored for low-resource languages. Consequently, there are only a few manually curated datasets. In this paper, we present a human curated sentence-level text simpl…
SentenceText SimplificationTransfer LearningVTechAGP: An Academic-to-General-Audience Text Paraphrase Dataset and Benchmark Models
Existing text simplification or paraphrase datasets mainly focus on sentence-level text generation in a general domain. These datasets are typically developed without using domain knowledge. In this paper, we release a n…
Language ModelingLanguage ModellingSentenceText Generation+1Attacking Misinformation Detection Using Adversarial Examples Generated by Language Models
We investigate the challenge of generating adversarial examples to test the robustness of text classification algorithms detecting low-credibility content, including propaganda, false claims, rumours and hyperpartisan ne…
ArticlesMisinformationRumour DetectionStyle Transfer+3SciGisPy: a Novel Metric for Biomedical Text Simplification via Gist Inference Score
Biomedical literature is often written in highly specialized language, posing significant comprehension challenges for non-experts. Automatic text simplification (ATS) offers a solution by making such texts more accessib…
ChunkingText SimplificationSociety of Medical Simplifiers
Medical text simplification is crucial for making complex biomedical literature more accessible to non-experts. Traditional methods struggle with the specialized terms and jargon of medical texts, lacking the flexibility…
PhilosophyText SimplificationLabel Confidence Weighted Learning for Target-level Sentence Simplification
Multi-level sentence simplification generates simplified sentences with varying language proficiency levels. We propose Label Confidence Weighted Learning (LCWL), a novel approach that incorporates a label confidence wei…
DecoderSentenceText Simplification