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Compositional Sequence Labeling Models for Error Detection in Learner Writing

arXiv 1607.06153 ↗First posted 20 Jul 2016cs.CL cs.NEcited by 16

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Abstract (arXiv)

In this paper, we present the first experiments using neural network models for the task of error detection in learner writing. We perform a systematic comparison of alternative compositional architectures and propose a framework for error detection based on bidirectional LSTMs. Experiments on the CoNLL-14 shared task dataset show the model is able to outperform other participants on detecting errors in learner writing. Finally, the model is integrated with a publicly deployed self-assessment system, leading to performance comparable to human annotators.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Jul 2016.

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Citing papers per year: 2021: 5; 2022: 3; 2023: 3; 2024: 4; 2025: 1.

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  1. 2024A Design Space for Intelligent and Interactive Writing Assistantscited by 76
  2. 2021What to Pre-Train on? Efficient Intermediate Task Selectioncited by 62
  3. 2022Grammatical Error Correction: A Survey of the State of the Artcited by 43
  4. 2022SynGEC: Syntax-Enhanced Grammatical Error Correction with a Tailored GEC-Oriented Parsercited by 32
  5. 2023Advancements in Arabic Grammatical Error Detection and Correction: An Empirical Investigationcited by 22
  6. 2021Automated scholarly paper review: Concepts, technologies, and challengescited by 21
  7. 2023Data Cleaning and Machine Learning: A Systematic Literature Reviewcited by 9
  8. 2025Opportunities and Challenges of LLMs in Education: An NLP Perspectivecited by 6
  9. 2021Zero-shot Sequence Labeling for Transformer-based Sentence Classifierscited by 5
  10. 2024Oddballness: universal anomaly detection with language modelscited by 2
  11. 2021Combining GCN and Transformer for Chinese Grammatical Error Detectioncited by 1
  12. 2023Finding the Needle in a Haystack: Unsupervised Rationale Extraction from Long Text Classifierscited by 1
4 more
  1. 2024Detection-Correction Structure via General Language Model for Grammatical Error Correctioncited by 1
  2. 2021Development of an Extractive Title Generation System Using Titles of Papers of Top Conferences for Intermediate English Studentscited by 0
  3. 2022Approximate Conditional Coverage & Calibration via Neural Model Approximationscited by 0
  4. 2024Zero-shot Cross-Lingual Transfer for Synthetic Data Generation in Grammatical Error Detectioncited by 0