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 1–10 of 468 papers

TitleStatusHype
Document-Level Text Generation with Minimum Bayes Risk Decoding using Optimal TransportCode0
Enhancing Paraphrase Type Generation: The Impact of DPO and RLHF Evaluated with Human-Ranked DataCode0
Resource for Error Analysis in Text Simplification: New Taxonomy and Test Collection—0
Automated Feedback Loops to Protect Text Simplification with Generative AI from Information Loss—0
A Structured Literature Review on Traditional Approaches in Current Natural Language Processing—0
LLM-based Text Simplification and its Effect on User Comprehension and Cognitive Load—0
SimplifyMyText: An LLM-Based System for Inclusive Plain Language Text Simplification—0
Evaluation Under Imperfect Benchmarks and Ratings: A Case Study in Text Simplification—0
Automatic Input Rewriting Improves Translation with Large Language ModelsCode1
Aligning Sentence Simplification with ESL Learner's Proficiency for Language AcquisitionCode0
Show:102550
← PrevPage 1 of 47Next →
All datasetsTurkCorpusASSETNewselaPWKP / WikiSmallDEplain-APA-docDEplain-web-docEurekaAlertDEplain-APA-sentDEplain-web-sentWikiLargeFRWiki-Auto + Turk

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1mT5 (fine-tuned on MULTI-SIM)SARI39.23—Unverified
2LSTMSARI39.05—Unverified