# Some Grammatical Errors are Frequent, Others are Important

arXiv: https://arxiv.org/abs/2205.05730 · HTML: https://mlsanity.com/paper/2205.05730/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 22 references that are in the map.
- First posted on arXiv 11 May 2022.

## Builds on (most cited first, 6 of 6)

- [JFLEG: A Fluency Corpus and Benchmark for Grammatical Error Correction](https://mlsanity.com/paper/1702.04066/) (2017)
- [Automatic Metric Validation for Grammatical Error Correction](https://mlsanity.com/paper/1804.11225/) (2018)
- [A Comprehensive Survey of Grammar Error Correction](https://mlsanity.com/paper/2005.06600/) (2020)
- [Inherent Biases in Reference based Evaluation for Grammatical Error Correction and Text Simplification](https://mlsanity.com/paper/1804.11254/) (2018)
- [Classifying Syntactic Errors in Learner Language](https://mlsanity.com/paper/2010.11032/) (2020)
- [SERRANT: a syntactic classifier for English Grammatical Error Types](https://mlsanity.com/paper/2104.02310/) (2021)

## Abstract (arXiv)

In Grammatical Error Correction, systems are evaluated by the number of errors they correct. However, no one has assessed whether all error types are equally important. We provide and apply a method to quantify the importance of different grammatical error types to humans. We show that some rare errors are considered disturbing while other common ones are not. This affects possible directions to improve both systems and their evaluation.