mlsanityData to 14 Oct 2026

gec-metrics: A Unified Library for Grammatical Error Correction Evaluation

arXiv 2505.19388 ↗First posted 26 May 2025cs.CLcited by 9

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Abstract (arXiv)

We introduce gec-metrics, a library for using and developing grammatical error correction (GEC) evaluation metrics through a unified interface. Our library enables fair system comparisons by ensuring that everyone conducts evaluations using a consistent implementation. Moreover, it is designed with a strong focus on API usage, making it highly extensible. It also includes meta-evaluation functionalities and provides analysis and visualization scripts, contributing to developing GEC evaluation metrics. Our code is released under the MIT license and is also distributed as an installable package. The video is available on YouTube.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 15 of its 38 references that are in the map. First posted on arXiv 26 May 2025.

Builds on

15 of 38 references.

References · 15

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
  3. 2021BARTScore: Evaluating Generated Text as Text Generationcited by 722
  4. 2020GECToR -- Grammatical Error Correction: Tag, Not Rewritecited by 177
  5. 2021A Simple Recipe for Multilingual Grammatical Error Correctioncited by 108
  6. 2019Parallel Iterative Edit Models for Local Sequence Transductioncited by 81
  7. 2023Exploring Effectiveness of GPT-3 in Grammatical Error Correction: A Study on Performance and Controllability in Prompt-Based Methodscited by 37
  8. 2020Stronger Baselines for Grammatical Error Correction Using Pretrained Encoder-Decoder Modelcited by 33
  9. 2016GLEU Without Tuningcited by 24
  10. 2022Evaluate & Evaluation on the Hub: Better Best Practices for Data and Model Measurementscited by 22
  11. 2022Revisiting Grammatical Error Correction Evaluation and Beyondcited by 18
  12. 2024mbrs: A Library for Minimum Bayes Risk Decodingcited by 13
3 more
  1. 2017Grammatical Error Correction with Neural Reinforcement Learningcited by 7
  2. 2025Rethinking Evaluation Metrics for Grammatical Error Correction: Why Use a Different Evaluation Process than Human?cited by 7
  3. 2023Minimum Bayes' Risk Decoding for System Combination of Grammatical Error Correction Systemscited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 4; 2026: 5.

9 papers.

  1. 2025Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Abilitycited by 10
  2. 2025IMPARA-GED: Grammatical Error Detection is Boosting Reference-free Grammatical Error Quality Estimatorcited by 2
  3. 2026Edit-level Majority Voting Mitigates Over-Correction in LLM-based Grammatical Error Correctioncited by 1
  4. 2025Reliability Crisis of Reference-free Metrics for Grammatical Error Correctioncited by 0
  5. 2025IndicGEC: Powerful Models, or a Measurement Mirage?cited by 0
  6. 2026Grammatical Error Correction Evaluation by Optimally Transporting Edit Representationcited by 0
  7. 2026Incentives Of EdTech: A Systematic Review Of EduNLP Researchcited by 0
  8. 2026Larger Context Window, Fewer Overcorrections: Optimizing Prompts and Batching for Minimal-Edit Grammatical Error Correctioncited by 0
  9. 2026Don't Count the Edits, Judge by the Outcome Alone: Reward-Based Evaluation for Grammatical Error Correctioncited by 0