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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 151–200 of 468 papers

TitleStatusHype
Predicting Sentence Deletions for Text Simplification Using a Functional Discourse Structure—0
On the Ethical Considerations of Text Simplification—0
SimpleBERT: A Pre-trained Model That Learns to Generate Simple Words—0
Evaluating Factuality in Text SimplificationCode0
Text Revision by On-the-Fly Representation OptimizationCode0
Learning to Simplify with Data Hopelessly Out of Alignment—0
An Imitation Learning Curriculum for Text Editing with Non-Autoregressive Models—0
The Common Readability Formula & Five Adjusted Readability Formulas for Text Simplification, Medical Documents and Other General Uses—0
Unsupervised Sentence Simplification via Dependency Parsing—0
Automatic Lexical Simplification for Turkish—0
Towards more patient friendly clinical notes through language models and ontologies—0
The (Un)Suitability of Automatic Evaluation Metrics for Text SimplificationCode0
Combining Paraphrase Pre-trained Model and Controllable Rules for Unsupervised Sentence Simplification—0
Few-shot Controllable Style Transfer for Low-Resource Multilinugal Settings—0
Divide-and-Conquer Text Simplification by Scalable Data Enhancement—0
A New Dataset and Efficient Baselines for Document-level Text Simplification in GermanCode0
Few-shot Controllable Style Transfer for Low-Resource Multilingual Settings—0
Text Simplification for Comprehension-based Question-AnsweringCode0
How May I Help You? Using Neural Text Simplification to Improve Downstream NLP TasksCode0
A Syntax-Aware Edit-based System for Text Simplification—0
Exploring German Multi-Level Text SimplificationCode0
Flesch-Kincaid is Not a Text Simplification Evaluation Metric—0
Cartography of Natural Language Processing for Social Good (NLP4SG): Searching for Definitions, Statistics and White Spots—0
JUST-BLUE at SemEval-2021 Task 1: Predicting Lexical Complexity using BERT and RoBERTa Pre-trained Language Models—0
Automatic Text Simplification for Social Good: Progress and Challenges—0
A Non-Autoregressive Edit-Based Approach to Controllable Text Simplification—0
Automatic Sentence Simplification in Low Resource Settings for Urdu—0
Investigating Text Simplification EvaluationCode0
What Makes a Concept Complex? Measuring Conceptual Complexity as a Precursor for Text Simplification—0
Parallel Text Alignment and Monolingual Parallel Corpus Creation from Philosophical Texts for Text SimplificationCode0
Improving Human Text Simplification with Sentence Fusion—0
Simplification automatique de textes biomédicaux en français: lorsque des données précises de petite taille aident (French Biomedical Text Simplification : When Small and Precise Helps )—0
Creating an Aligned Russian Text Simplification Dataset from Language Learner Data—0
Finding Spoiler Bias in Tweets by Zero-shot Learning and Knowledge Distilling from Neural Text SimplificationCode0
Predicting Lexical Complexity in English Texts: The Complex 2.0 Dataset—0
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics—0
Simple-QE: Better Automatic Quality Estimation for Text Simplification—0
CUT: Controllable Unsupervised Text Simplification—0
SEMA: Text Simplification Evaluation through Semantic Alignment—0
French Biomedical Text Simplification: When Small and Precise Helps—0
On the Helpfulness of Document Context to Sentence SimplificationCode0
Leveraging Contextual Embeddings and Idiom Principle for Detecting Idiomaticity in Potentially Idiomatic Expressions—0
Semantic Structural Decomposition for Neural Machine TranslationCode0
Text Simplification with Reinforcement Learning Using Supervised Rewards on Grammaticality, Meaning Preservation, and Simplicity—0
Context-Aware Automatic Text Simplification of Health Materials in Low-Resource Domains—0
Controllable Text Simplification with Explicit Paraphrasing—0
Elaborative Simplification: Content Addition and Explanation Generation in Text SimplificationCode0
Seq2Edits: Sequence Transduction Using Span-level Edit OperationsCode0
Small but Mighty: New Benchmarks for Split and Rephrase—0
A Survey on Text Simplification—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