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A Report on the Complex Word Identification Shared Task 2018

arXiv 1804.09132 ↗First posted 24 Apr 2018cs.CLcited by 30

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Abstract (arXiv)

We report the findings of the second Complex Word Identification (CWI) shared task organized as part of the BEA workshop co-located with NAACL-HLT'2018. The second CWI shared task featured multilingual and multi-genre datasets divided into four tracks: English monolingual, German monolingual, Spanish monolingual, and a multilingual track with a French test set, and two tasks: binary classification and probabilistic classification. A total of 12 teams submitted their results in different task/track combinations and 11 of them wrote system description papers that are referred to in this report and appear in the BEA workshop proceedings.

Key facts. Cited by 30 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Apr 2018.

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Citing papers per year: 2021: 9; 2022: 4; 2023: 5; 2024: 9; 2025: 0; 2026: 3.

30 papers.

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  1. 2023Findings of the TSAR-2022 Shared Task on Multilingual Lexical Simplificationcited by 20
  2. 2021SemEval-2021 Task 1: Lexical Complexity Predictioncited by 19
  3. 2022Lexical Simplification Benchmarks for English, Portuguese, and Spanishcited by 18
  4. 2021Predicting Lexical Complexity in English Texts: The Complex 2.0 Datasetcited by 15
  5. 2021A Survey on Using Gaze Behaviour for Natural Language Processingcited by 11
  6. 2022One Size Does Not Fit All: The Case for Personalised Word Complexity Modelscited by 10
  7. 2024Exploring Large Language Models to generate Easy to Read contentcited by 9
  8. 2023Japanese Lexical Complexity for Non-Native Readers: A New Datasetcited by 5
  9. 2024An LLM-Enhanced Adversarial Editing System for Lexical Simplificationcited by 5
  10. 2023Deep Learning Approaches to Lexical Simplification: A Surveycited by 4
  11. 2024Difficult for Whom? A Study of Japanese Lexical Complexitycited by 4
  12. 2024CoAM: Corpus of All-Type Multiword Expressionscited by 4
18 more
  1. 2021IITK@LCP at SemEval 2021 Task 1: Classification for Lexical Complexity Regression Taskcited by 3
  2. 2021LCP-RIT at SemEval-2021 Task 1: Exploring Linguistic Features for Lexical Complexity Predictioncited by 3
  3. 2022Domain Adaptation in Multilingual and Multi-Domain Monolingual Settings for Complex Word Identificationcited by 3
  4. 2023Lexical Complexity Prediction: An Overviewcited by 3
  5. 2024Investigating Large Language Models for Complex Word Identification in Multilingual and Multidomain Setupscited by 3
  6. 2021BigGreen at SemEval-2021 Task 1: Lexical Complexity Prediction with Assembly Modelscited by 2
  7. 2021MultiAzterTest: a Multilingual Analyzer on Multiple Levels of Language for Readability Assessmentcited by 2
  8. 2023Controllable Lexical Simplification for Englishcited by 2
  9. 2024Estimating Lexical Complexity from Document-Level Distributionscited by 2
  10. 2021Semi-Supervised Joint Estimation of Word and Document Readabilitycited by 1
  11. 2022SimpleBERT: A Pre-trained Model That Learns to Generate Simple Wordscited by 1
  12. 2024Lexical Complexity Prediction and Lexical Simplification for Catalan and Spanish: Resource Creation, Quality Assessment, and Ethical Considerationscited by 1
  13. 2024Readability-guided Idiom-aware Sentence Simplification (RISS) for Chinesecited by 1
  14. 2026RALS: Resources and Baselines for Romanian Automatic Lexical Simplificationcited by 1
  15. 2021OCHADAI-KYOTO at SemEval-2021 Task 1: Enhancing Model Generalization and Robustness for Lexical Complexity Predictioncited by 0
  16. 2024MultiLS: A Multi-task Lexical Simplification Frameworkcited by 0
  17. 2026Improving Lexical Difficulty Prediction with Context-Aligned Contrastive Learning and Ridge Ensemblingcited by 0
  18. 2026What makes a word hard to learn? Modeling L1 influence on English vocabulary difficultycited by 0