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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 251–300 of 468 papers

TitleStatusHype
Learning Simplifications for Specific Target Audiences—0
Learning to Simplify with Data Hopelessly Out of Alignment—0
Learning to Summarise Related Sentences—0
Aligning Texts and Knowledge Bases with Semantic Sentence Simplification—0
Leveraging Contextual Embeddings and Idiom Principle for Detecting Idiomaticity in Potentially Idiomatic Expressions—0
Lexi: A tool for adaptive, personalized text simplification—0
Lexical Complexity Prediction: An Overview—0
Lexical Simplification using multi level and modular approach—0
Lexical Substitution Dataset for German—0
Lexico-syntactic text simplification and compression with typed dependencies—0
LexSubNC: A Dataset of Lexical Substitution for Nominal Compounds—0
LLM-based Text Simplification and its Effect on User Comprehension and Cognitive Load—0
The descriptive approaches of the verb in Linguistics, Terminology and NLP (Les mod\`eles de description du verbe dans les travaux de Linguistique, Terminologie et TAL) [in French]—0
LTG at SemEval-2016 Task 11: Complex Word Identification with Classifier Ensembles—0
MacSaar at SemEval-2016 Task 11: Zipfian and Character Features for ComplexWord Identification—0
Making Biographical Data in Wikipedia Readable: A Pattern-based Multilingual Approach—0
Making historical texts accessible to everybody—0
MANTIS at TSAR-2022 Shared Task: Improved Unsupervised Lexical Simplification with Pretrained Encoders—0
MaskEval: Weighted MLM-Based Evaluation for Text Summarization and Simplification—0
MAZA at SemEval-2016 Task 11: Detecting Lexical Complexity Using a Decision Stump Meta-Classifier—0
Aligning Sentences from Standard Wikipedia to Simple Wikipedia—0
The Fewer Splits are Better: Deconstructing Readability in Sentence Splitting—0
A Lightweight Regression Method to Infer Psycholinguistic Properties for Brazilian Portuguese—0
The Fewer, the Better? A Contrastive Study about Ways to Simplify—0
Medical text simplification using synonym replacement: Adapting assessment of word difficulty to a compounding language—0
A Leveled Reading Corpus of Modern Standard Arabic—0
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics—0
Melbourne at SemEval 2016 Task 11: Classifying Type-level Word Complexity using Random Forests with Corpus and Word List Features—0
Metaphors in Text Simplification: To change or not to change, that is the question—0
The Impact of Rule-Based Text Generation on the Quality of Abstractive Summaries—0
MinWikiSplit: A Sentence Splitting Corpus with Minimal Propositions—0
The Interface Between Readability and Automatic Text Simplification—0
Modeling Language Proficiency Using Implicit Feedback—0
Modeling the Readability of German Targeting Adults and Children: An empirically broad analysis and its cross-corpus validation—0
Monolingual sentence matching for text simplification—0
M-Ped: Multi-Prompt Ensemble Decoding for Large Language Models—0
The Lay Person's Guide to Biomedicine: Orchestrating Large Language Models—0
Alector: A Parallel Corpus of Simplified French Texts with Alignments of Misreadings by Poor and Dyslexic Readers—0
MultiLS: A Multi-task Lexical Simplification Framework—0
MUSST: A Multilingual Syntactic Simplification Tool—0
The Promise and Challenges of Using LLMs to Accelerate the Screening Process of Systematic Reviews—0
Negative Lexically Constrained Decoding for Paraphrase Generation—0
A Keyword-based Monolingual Sentence Aligner in Text Simplification—0
Neural Machine Translation from Simplified Translations—0
A Hybrid System for Spanish Text Simplification—0
Neural Text Simplification in Low-Resource Conditions Using Weak Supervision—0
The SAMER Arabic Text Simplification Corpus—0
Neural Versus Non-Neural Text Simplification: A Case Study—0
NILC at CWI 2018: Exploring Feature Engineering and Feature Learning—0
Noisy Channel for Automatic 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