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Enhancing Grammatical Error Correction Systems with Explanations

arXiv 2305.15676 ↗First posted 25 May 2023cs.CLcited by 19

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Abstract (arXiv)

Grammatical error correction systems improve written communication by detecting and correcting language mistakes. To help language learners better understand why the GEC system makes a certain correction, the causes of errors (evidence words) and the corresponding error types are two key factors. To enhance GEC systems with explanations, we introduce EXPECT, a large dataset annotated with evidence words and grammatical error types. We propose several baselines and analysis to understand this task. Furthermore, human evaluation verifies our explainable GEC system's explanations can assist second-language learners in determining whether to accept a correction suggestion and in understanding the associated grammar rule.

Key facts. Cited by 19 papers in the map (data through 14 Oct 2026). Builds on 14 of its 29 references that are in the map. First posted on arXiv 25 May 2023.

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14 of 29 references.

References · 14

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  3. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
  4. 2019Generalization through Memorization: Nearest Neighbor Language Modelscited by 800
  5. 2018AllenNLP: A Deep Semantic Natural Language Processing Platformcited by 347
  6. 2016Deep Biaffine Attention for Neural Dependency Parsingcited by 334
  7. 2020GECToR -- Grammatical Error Correction: Tag, Not Rewritecited by 177
  8. 2021A Simple Recipe for Multilingual Grammatical Error Correctioncited by 108
  9. 2019Parallel Iterative Edit Models for Local Sequence Transductioncited by 81
  10. 2021Synthetic Data Generation for Grammatical Error Correction with Tagged Corruption Modelscited by 56
  11. 2018Stack-Pointer Networks for Dependency Parsingcited by 36
  12. 2022SynGEC: Syntax-Enhanced Grammatical Error Correction with a Tailored GEC-Oriented Parsercited by 32
2 more
  1. 2022Interpretability for Language Learners Using Example-Based Grammatical Error Correctioncited by 13
  2. 2022Ensembling and Knowledge Distilling of Large Sequence Taggers for Grammatical Error Correctioncited by 12

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 5; 2025: 10; 2026: 2.

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  1. 2023GEE! Grammar Error Explanation with Large Language Modelscited by 15
  2. 2024How Ready Are Generative Pre-trained Large Language Models for Explaining Bengali Grammatical Errors?cited by 11
  3. 2023Controlled Generation with Prompt Insertion for Natural Language Explanations in Grammatical Error Correctioncited by 7
  4. 2025Position: LLMs Can be Good Tutors in English Educationcited by 6
  5. 2024Gazelle: An Instruction Dataset for Arabic Writing Assistancecited by 4
  6. 2024Efficient and Interpretable Grammatical Error Correction with Mixture of Expertscited by 3
  7. 2025Scaling and Prompting for Improved End-to-End Spoken Grammatical Error Correctioncited by 2
  8. 2025Annotating Errors in English Learners' Written Language Production: Advancing Automated Written Feedback Systemscited by 2
  9. 2026MedErrBench: A Fine-Grained Multilingual Benchmark for Medical Error Detection and Correction with Clinical Expert Annotationscited by 2
  10. 2025Explanation based In-Context Demonstrations Retrieval for Multilingual Grammatical Error Correctioncited by 1
  11. 2025End-to-End Spoken Grammatical Error Correctioncited by 1
  12. 2024Leveraging Biases in Large Language Models: "bias-kNN'' for Effective Few-Shot Learningcited by 0
7 more
  1. 2024Zero-shot Cross-Lingual Transfer for Synthetic Data Generation in Grammatical Error Detectioncited by 0
  2. 2025KSOD: Knowledge Supplement for LLMs On Demandcited by 0
  3. 2025Leveraging Prompt-Tuning for Bengali Grammatical Error Explanation Using Large Language Modelscited by 0
  4. 2025COLA-GEC: A Bidirectional Framework for Enhancing Grammatical Acceptability and Error Correctioncited by 0
  5. 2025RE2: Improving Chinese Grammatical Error Correction via Retrieving Appropriate Examples with Explanationcited by 0
  6. 2025Time Is Effort: Estimating Human Post-Editing Time for Grammar Error Correction Tool Evaluationcited by 0
  7. 2026Encode Errors: Representational Retrieval of In-Context Demonstrations for Multilingual Grammatical Error Correctioncited by 0