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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
IAPUCP at SemEval-2021 Task 1: Stacking Fine-Tuned Transformers is Almost All You Need for Lexical Complexity Prediction—0
Manchester Metropolitan at SemEval-2021 Task 1: Convolutional Networks for Complex Word Identification—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
Personalizing Lexical Simplification—0
Personalized Text Retrieval for Learners of Chinese as a Foreign Language—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
Simplification Using Paraphrases and Context-Based Lexical Substitution—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
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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