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Lexical Simplification
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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
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Investigating Large Language Models for Complex Word Identification in Multilingual and Multidomain Setups
MultiLS-SP/CA: Lexical Complexity Prediction and Lexical Simplification Resources for Catalan and Spanish
An LLM-Enhanced Adversarial Editing System for Lexical Simplification
MultiLS: A Multi-task Lexical Simplification Framework
Unsupervised Lexical Simplification with Context Augmentation
On the Automatic Generation and Simplification of Children's Stories
Multilingual Lexical Simplification via Paraphrase Generation
Multilingual Controllable Transformer-Based Lexical Simplification
Teaching the Pre-trained Model to Generate Simple Texts for Text Simplification
Deep Learning Approaches to Lexical Simplification: A Survey
Findings of the TSAR-2022 Shared Task on Multilingual Lexical Simplification
Controllable Lexical Simplification for English
Lexical Simplification using multi level and modular approach
UniHD at TSAR-2022 Shared Task: Is Compute All We Need for Lexical Simplification?
MANTIS at TSAR-2022 Shared Task: Improved Unsupervised Lexical Simplification with Pretrained Encoders
ALEXSIS-PT: A New Resource for Portuguese Lexical Simplification
Lexical Simplification Benchmarks for English, Portuguese, and Spanish
Towards Arabic Sentence Simplification via Classification and Generative Approaches
SimpleBERT: A Pre-trained Model That Learns to Generate Simple Words
Automatic Lexical Simplification for Turkish
Enhancing Pre-trained Language Model with Lexical Simplification
Chinese Lexical Simplification
LSBert: A Simple Framework for Lexical Simplification
Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Lexical Simplification with Pretrained Encoders
A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification
Improving Neural Text Simplification Model with Simplified Corpora
Adversarial Propagation and Zero-Shot Cross-Lingual Transfer of Word Vector Specialization
Prior Attention for Style-aware Sequence-to-Sequence Models
A Knowledge-Based Approach to Word Sense Disambiguation by distributional selection and semantic features
Approches d'analyse distributionnelle pour améliorer la désambiguïsation sémantique
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.