SOTAVerified

Text Simplification

Text Simplification is the task of reducing the complexity of the vocabulary and sentence structure of text while retaining its original meaning, with the goal of improving readability and understanding. Simplification has a variety of important societal applications, for example increasing accessibility for those with cognitive disabilities such as aphasia, dyslexia, and autism, or for non-native speakers and children with reading difficulties.

Source: Multilingual Unsupervised Sentence Simplification

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–250 of 468 papers

TitleStatusHype
French and German Corpora for Audience-based Text Type Classification—0
French Biomedical Text Simplification: When Small and Precise Helps—0
From distributional semantics to feature norms: grounding semantic models in human perceptual data—0
From Shakespeare to Twitter: What are Language Styles all about?—0
Generating Animations from Screenplays—0
Text Simplification as Tree Labeling—0
Text Simplification as Tree Transduction—0
HECTOR: A Hybrid TExt SimplifiCation TOol for Raw Texts in French—0
HMC at SemEval-2016 Task 11: Identifying Complex Words Using Depth-limited Decision Trees—0
A Corpus of Text Data and Gaze Fixations from Autistic and Non-Autistic Adults—0
Controlling Pre-trained Language Models for Grade-Specific Text Simplification—0
UWB at SemEval-2016 Task 11: Exploring Features for Complex Word Identification—0
Hybrid Simplification using Deep Semantics and Machine Translation—0
Hybrid text simplification using synchronous dependency grammars with hand-written and automatically harvested rules—0
Identification of Parallel Sentences in Comparable Monolingual Corpora from Different Registers—0
Identifying Abstract and Concrete Words in French to Better Address Reading Difficulties—0
Improvements to Dependency Parsing Using Automatic Simplification of Data—0
Improving Estonian Text Simplification through Pretrained Language Models and Custom Datasets—0
Improving Human Text Simplification with Sentence Fusion—0
Analysing Zero-Shot Readability-Controlled Sentence Simplification—0
Improving Machine Translation of English Relative Clauses with Automatic Text Simplification—0
Improving Neural Text Simplification Model with Simplified Corpora—0
Improving Text Simplification Language Modeling Using Unsimplified Text Data—0
Text Simplification from Professionally Produced Corpora—0
Text Simplification of College Admissions Instructions: A Professionally Simplified and Verified Corpus—0
Text Simplification of Scientific Texts for Non-Expert Readers—0
Input Seed Features for Guiding the Generation Process: A Statistical Approach for Spanish—0
Text Simplification to Help Individuals with Low Vision Read More Fluently—0
Text Simplification Tools for Spanish—0
Is Character Trigram Overlapping Ratio Still the Best Similarity Measure for Aligning Sentences in a Paraphrased Corpus?—0
Is it Possible to Modify Text to a Target Readability Level? An Initial Investigation Using Zero-Shot Large Language Models—0
An Adaptable Lexical Simplification Architecture for Major Ibero-Romance Languages—0
Joint Copying and Restricted Generation for Paraphrase—0
JUST-BLUE at SemEval-2021 Task 1: Predicting Lexical Complexity using BERT and RoBERTa Pre-trained Language Models—0
A Multilingual Simplified Language News Corpus—0
A multi-lingual and cross-domain analysis of features for text simplification—0
AmritaCEN at SemEval-2016 Task 11: Complex Word Identification using Word Embedding—0
Korean L2 Vocabulary Prediction: Can a Large Annotated Corpus be Used to Train Better Models for Predicting Unknown Words?—0
Label Confidence Weighted Learning for Target-level Sentence Simplification—0
Text simplification using synchronous dependency grammars: Generalising automatically harvested rules—0
Language Resources in Spanish for Automatic Text Simplification across Domains—0
Language Transfer Learning for Supervised Lexical Substitution—0
Text Simplification with Reinforcement Learning Using Supervised Rewards on Grammaticality, Meaning Preservation, and Simplicity—0
A model to predict lexical complexity and to grade words (Un mod\`ele pour pr\'edire la complexit\'e lexicale et graduer les mots) [in French]—0
The Common Readability Formula & Five Adjusted Readability Formulas for Text Simplification, Medical Documents and Other General Uses—0
LaSTUS/TALN at Complex Word Identification (CWI) 2018 Shared Task—0
LC-Score: Reference-less estimation of Text Comprehension Difficulty—0
Learning a Lexical Simplifier Using Wikipedia—0
The C-Score -- Proposing a Reading Comprehension Metrics as a Common Evaluation Measure for Text Simplification—0
Learning Paraphrasing for Multiword Expressions—0
Show:102550
← PrevPage 5 of 10Next →
All datasetsTurkCorpusASSETNewselaPWKP / WikiSmallDEplain-APA-docDEplain-web-docEurekaAlertDEplain-APA-sentDEplain-web-sentWikiLargeFRWiki-Auto + Turk

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GPT-175B (6 SARI-selected examples, high/low)SARI (EASSE>=0.2.1)43.46—Unverified
2MUSS (BART+ACCESS Supervised)SARI (EASSE>=0.2.1)42.53—Unverified
3Control Prefixes (BART)SARI (EASSE>=0.2.1)42.32—Unverified
4TSTSARI (EASSE>=0.2.1)41.46—Unverified
5ACCESSSARI (EASSE>=0.2.1)41.38—Unverified
6MUSS (BART+ACCESS Unsupervised)SARI (EASSE>=0.2.1)40.85—Unverified
7DMASS-DCSSSARI (EASSE>=0.2.1)40.45—Unverified
8SBMT-SARISARI (EASSE>=0.2.1)39.56—Unverified
9EditNTSSARI (EASSE>=0.2.1)38.22—Unverified
10PBMT-RSARI (EASSE>=0.2.1)38.04—Unverified
#ModelMetricClaimedVerifiedStatus
1GPT-175B (15 SARI-selected examples, random ordering)BLEU73.92—Unverified
2MUSS (BART+ACCESS Supervised)BLEU72.98—Unverified
3Control Prefixes (BART)SARI (EASSE>=0.2.1)43.58—Unverified
4TSTSARI (EASSE>=0.2.1)43.21—Unverified
5MUSS (BART+ACCESS Unsupervised)SARI (EASSE>=0.2.1)42.65—Unverified
6ACCESSSARI (EASSE>=0.2.1)40.13—Unverified
7DMASS-DCSSSARI (EASSE>=0.2.1)38.67—Unverified
8Dress-LSSARI (EASSE>=0.2.1)36.59—Unverified
9UNTS (Unsupervised)SARI (EASSE>=0.2.1)35.19—Unverified
10PBMT-RSARI (EASSE>=0.2.1)34.63—Unverified
#ModelMetricClaimedVerifiedStatus
1CRF Alignment + TransformerSARI36.6—Unverified
2Pointer + Multi-task Entailment and Paraphrase GenerationSARI33.22—Unverified
3EditNTSSARI31.41—Unverified
4S2S-Cluster-FASARI30.73—Unverified
5Edit-Unsup-TSSARI30.44—Unverified
6NSELSTM-SSARI29.58—Unverified
7NSELSTM-BSARI27.42—Unverified
8DRESSSARI27.37—Unverified
9DMASS + DCSSSARI27.28—Unverified
10DRESS-LSSARI26.63—Unverified
#ModelMetricClaimedVerifiedStatus
1NSELSTM-BBLEU53.42—Unverified
2TSTSARI44.67—Unverified
3UNSUPBLEU38.47—Unverified
4DRESS-LSBLEU36.32—Unverified
5DRESSBLEU34.53—Unverified
6EditNTSSARI32.35—Unverified
7NSELSTM-SBLEU29.72—Unverified
8Pointer + Multi-task Entailment and Paraphrase GenerationBLEU27.23—Unverified
#ModelMetricClaimedVerifiedStatus
1long-mBART (trained on DEplain-APA-doc)SARI (EASSE>=0.2.1)44.56—Unverified
2long-mBART (trained on DEplain-APA-doc & DEplain-web-doc)SARI (EASSE>=0.2.1)42.86—Unverified
3long-mBART (trained on DEplain-web-doc)SARI (EASSE>=0.2.1)35.02—Unverified
#ModelMetricClaimedVerifiedStatus
1long-mBART (trained on DEplain-APA-doc & DEplain-web-doc)SARI (EASSE>=0.2.1)49.75—Unverified
2long-mBART (trained on DEplain-web-doc)SARI (EASSE>=0.2.1)49.58—Unverified
3long-mBART (trained on DEplain-APA-doc)SARI (EASSE>=0.2.1)43.09—Unverified
#ModelMetricClaimedVerifiedStatus
1SATSSARI40.83—Unverified
2MedTSS-BART (Without Training)Rouge135.17—Unverified
3HTSSRouge121.94—Unverified
#ModelMetricClaimedVerifiedStatus
1mBART (trained on DEplain-APA-sent & DEplain-web-sent)SARI (EASSE>=0.2.1)34.9—Unverified
2mBART (trained on DEplain-APA-sent)SARI (EASSE>=0.2.1)34.82—Unverified
#ModelMetricClaimedVerifiedStatus
1mBART (trained on DEplain-APA-sent & DEplain-web-sent)SARI (EASSE>=0.2.1)34.83—Unverified
2mBART (trained on DEplain-APA-sent)SARI (EASSE>=0.2.1)30.87—Unverified
#ModelMetricClaimedVerifiedStatus
1mT5 (fine-tuned on MULTI-SIM)SARI39.23—Unverified
2LSTMSARI39.05—Unverified
#ModelMetricClaimedVerifiedStatus
1BART (TextBox 2.0)BLEU-490.81—Unverified