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Complex Word Identification

Identifying difficult words or expressions in a text.

Papers

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Showing 1–50 of 67 papers

TitleStatusHype
New Evaluation Paradigm for Lexical Simplification—0
Investigating Large Language Models for Complex Word Identification in Multilingual and Multidomain SetupsCode0
Difficult for Whom? A Study of Japanese Lexical ComplexityCode0
A User-Centered Evaluation of Spanish Text SimplificationCode0
Complex Word Identification in Vietnamese: Towards Vietnamese Text Simplification—0
CWID-hi: A Dataset for Complex Word Identification in Hindi Text—0
Domain Adaptation in Multilingual and Multi-Domain Monolingual Settings for Complex Word Identification—0
One Size Does Not Fit All: The Case for Personalised Word Complexity Models—0
A Survey on Using Gaze Behaviour for Natural Language Processing—0
CLexIS2: A New Corpus for Complex Word Identification Research in Computing Studies—0
Manchester Metropolitan at SemEval-2021 Task 1: Convolutional Networks for Complex Word Identification—0
IAPUCP at SemEval-2021 Task 1: Stacking Fine-Tuned Transformers is Almost All You Need for Lexical Complexity Prediction—0
cs60075_team2 at SemEval-2021 Task 1 : Lexical Complexity Prediction using Transformer-based Language Models pre-trained on various text corporaCode0
Predicting Lexical Complexity in English Texts: The Complex 2.0 Dataset—0
Cross-Lingual Transfer Learning for Complex Word Identification—0
Interpreting Neural CWI Classifiers' Weights as Vocabulary Size—0
Detecting Multiword Expression Type Helps Lexical Complexity AssessmentCode0
SeCoDa: Sense Complexity Dataset—0
CompLex --- A New Corpus for Lexical Complexity Prediction from Likert Scale Data—0
CompLex: A New Corpus for Lexical Complexity Prediction from Likert Scale DataCode0
Multilingual Complex Word Identification: Convolutional Neural Networks with Morphological and Linguistic Features—0
Comparative judgments are more consistent than binary classification for labelling word complexity—0
Complex Word Identification as a Sequence Labelling TaskCode0
Strong Baselines for Complex Word Identification across Multiple LanguagesCode0
The Interface Between Readability and Automatic Text Simplification—0
Personalized Text Retrieval for Learners of Chinese as a Foreign Language—0
Personalizing Lexical Simplification—0
Deep Learning Architecture for Complex Word Identification—0
SB@GU at the Complex Word Identification 2018 Shared Task—0
Complex Word Identification Based on Frequency in a Learner Corpus—0
Complex Word Identification: Convolutional Neural Network vs. Feature Engineering—0
The Whole is Greater than the Sum of its Parts: Towards the Effectiveness of Voting Ensemble Classifiers for Complex Word Identification—0
Complex Word Identification Using Character n-grams—0
Cross-lingual complex word identification with multitask learning—0
CAMB at CWI Shared Task 2018: Complex Word Identification with Ensemble-Based Voting—0
LaSTUS/TALN at Complex Word Identification (CWI) 2018 Shared Task—0
NILC at CWI 2018: Exploring Feature Engineering and Feature Learning—0
NT2Lex: A CEFR-Graded Lexical Resource for Dutch as a Foreign Language Linked to Open Dutch WordNet—0
Simplification Using Paraphrases and Context-Based Lexical Substitution—0
A Report on the Complex Word Identification Shared Task 2018—0
UnibucKernel: A kernel-based learning method for complex word identification—0
CWIG3G2 - Complex Word Identification Task across Three Text Genres and Two User Groups—0
Complex Word Identification: Challenges in Data Annotation and System Performance—0
CLaC at SemEval-2016 Task 11: Exploring linguistic and psycho-linguistic Features for Complex Word Identification—0
Multilingual and Cross-Lingual Complex Word Identification—0
Lexical Simplification with Neural Ranking—0
Understanding the Lexical Simplification Needs of Non-Native Speakers of English—0
UWB at SemEval-2016 Task 11: Exploring Features for Complex Word Identification—0
AmritaCEN at SemEval-2016 Task 11: Complex Word Identification using Word Embedding—0
CoastalCPH at SemEval-2016 Task 11: The importance of designing your Neural Networks right—0
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