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

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Showing 101–150 of 468 papers

TitleStatusHype
Dancing Between Success and Failure: Edit-level Simplification Evaluation using SALSA—0
Language Models for German Text Simplification: Overcoming Parallel Data Scarcity through Style-specific Pre-trainingCode0
Teaching the Pre-trained Model to Generate Simple Texts for Text SimplificationCode0
Multilingual Simplification of Medical TextsCode0
DiffuSIA: A Spiral Interaction Architecture for Encoder-Decoder Text Diffusion—0
Reducing Sequence Length by Predicting Edit Operations with Large Language Models—0
Deep Learning Approaches to Lexical Simplification: A Survey—0
Elaborative Simplification as Implicit Questions Under Discussion—0
Context-Aware Document SimplificationCode0
ChatGPT as a Text Simplification Tool to Remove Bias—0
Syntactic Complexity Identification, Measurement, and Reduction Through Controlled Syntactic SimplificationCode0
SimpLex: a lexical text simplification architectureCode0
RISC: Generating Realistic Synthetic Bilingual Insurance ContractCode0
Lexical Complexity Prediction: An Overview—0
Prompt-based Learning for Text Readability AssessmentCode0
Med-EASi: Finely Annotated Dataset and Models for Controllable Simplification of Medical TextsCode0
Exploiting Summarization Data to Help Text SimplificationCode0
NapSS: Paragraph-level Medical Text Simplification via Narrative Prompting and Sentence-matching SummarizationCode0
Findings of the TSAR-2022 Shared Task on Multilingual Lexical Simplification—0
Lexical Simplification using multi level and modular approach—0
Mitigating Data Scarcity for Large Language ModelsCode0
The Fewer Splits are Better: Deconstructing Readability in Sentence Splitting—0
Traditional Readability Formulas Compared for English—0
Automatic Text Simplification of News Articles in the Context of Public Broadcasting—0
(Psycho-)Linguistic Features Meet Transformer Models for Improved Explainable and Controllable Text Simplification—0
MANTIS at TSAR-2022 Shared Task: Improved Unsupervised Lexical Simplification with Pretrained Encoders—0
Patient-friendly Clinical Notes: Towards a new Text Simplification DatasetCode0
Cognitive Simplification Operations Improve Text SimplificationCode0
Noisy Channel for Automatic Text Simplification—0
Is Character Trigram Overlapping Ratio Still the Best Similarity Measure for Aligning Sentences in a Paraphrased Corpus?—0
Arabic Word-level Readability Visualization for Assisted Text Simplification—0
Shallow Discourse Parsing for Open Information Extraction and Text Simplification—0
Text Simplification of College Admissions Instructions: A Professionally Simplified and Verified Corpus—0
Unsupervised Simplification of Legal Texts—0
Pseudo-Labels Are All You Need—0
Sequence to sequence pretraining for a less-resourced Slovenian languageCode0
Complex Word Identification in Vietnamese: Towards Vietnamese Text Simplification—0
An Evaluation of Binary Comparative Lexical Complexity Models—0
Unsupervised Sentence Simplification via Dependency ParsingCode0
The Swedish Simplification Toolkit: – Designed with Target Audiences in Mind—0
Towards Readability-Controlled Machine Translation of COVID-19 Texts—0
Open corpora and toolkit for assessing text readability in FrenchCode0
Evaluation of Automatic Text Simplification: Where are we now, where should we go from here—0
HECTOR: A Hybrid TExt SimplifiCation TOol for Raw Texts in French—0
A Multilingual Simplified Language News Corpus—0
CWID-hi: A Dataset for Complex Word Identification in Hindi Text—0
MaskEval: Weighted MLM-Based Evaluation for Text Summarization and Simplification—0
Lossless Acceleration for Seq2seq Generation with Aggressive DecodingCode0
Domain Adaptation in Multilingual and Multi-Domain Monolingual Settings for Complex Word Identification—0
One Size Does Not Fit All: The Case for Personalised Word Complexity Models—0
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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