Lexical Simplification

19 papers with code • 0 benchmarks • 1 datasets

The goal of Lexical Simplification is to replace complex words (typically words that are used less often in language and are therefore less familiar to readers) with their simpler synonyms, without infringing the grammaticality and changing the meaning of the text.

Source: Adversarial Propagation and Zero-Shot Cross-Lingual Transfer of Word Vector Specialization

Datasets


Latest papers with no code

An LLM-Enhanced Adversarial Editing System for Lexical Simplification

no code yet • 22 Feb 2024

Lexical Simplification (LS) aims to simplify text at the lexical level.

MultiLS: A Multi-task Lexical Simplification Framework

no code yet • 22 Feb 2024

We present MultiLS, the first LS framework that allows for the creation of a multi-task LS dataset.

On the Automatic Generation and Simplification of Children's Stories

no code yet • 27 Oct 2023

With recent advances in large language models (LLMs), the concept of automatically generating children's educational materials has become increasingly realistic.

Deep Learning Approaches to Lexical Simplification: A Survey

no code yet • 19 May 2023

To reflect these recent advances, we present a comprehensive survey of papers published between 2017 and 2023 on LS and its sub-tasks with a special focus on deep learning.

Findings of the TSAR-2022 Shared Task on Multilingual Lexical Simplification

no code yet • 6 Feb 2023

We report findings of the TSAR-2022 shared task on multilingual lexical simplification, organized as part of the Workshop on Text Simplification, Accessibility, and Readability TSAR-2022 held in conjunction with EMNLP 2022.

Lexical Simplification using multi level and modular approach

no code yet • 3 Feb 2023

Text Simplification is an ongoing problem in Natural Language Processing, solution to which has varied implications.

MANTIS at TSAR-2022 Shared Task: Improved Unsupervised Lexical Simplification with Pretrained Encoders

no code yet • 19 Dec 2022

In this paper we present our contribution to the TSAR-2022 Shared Task on Lexical Simplification of the EMNLP 2022 Workshop on Text Simplification, Accessibility, and Readability.

ALEXSIS-PT: A New Resource for Portuguese Lexical Simplification

no code yet • COLING 2022

To continue improving the performance of LS systems we introduce ALEXSIS-PT, a novel multi-candidate dataset for Brazilian Portuguese LS containing 9, 605 candidate substitutions for 387 complex words.

Towards Arabic Sentence Simplification via Classification and Generative Approaches

no code yet • 20 Apr 2022

This paper presents an attempt to build a Modern Standard Arabic (MSA) sentence-level simplification system.

SimpleBERT: A Pre-trained Model That Learns to Generate Simple Words

no code yet • 16 Apr 2022

We use a small-scale simple text dataset for continued pre-training and employ two methods to identify simple words from the texts.