Reference-less Measure of Faithfulness for Grammatical Error Correction
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Abstract (arXiv)
We propose USim, a semantic measure for Grammatical Error Correction (GEC) that measures the semantic faithfulness of the output to the source, thereby complementing existing reference-less measures (RLMs) for measuring the output's grammaticality. USim operates by comparing the semantic symbolic structure of the source and the correction, without relying on manually-curated references. Our experiments establish the validity of USim, by showing that (1) semantic annotation can be consistently applied to ungrammatical text; (2) valid corrections obtain a high USim similarity score to the source; and (3) invalid corrections obtain a lower score.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Apr 2018.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 2; 2024: 1; 2025: 1; 2026: 1.
9 papers.
- 2023Efficient Benchmarking of Language Modelscited by 71
- 2022Grammatical Error Correction: A Survey of the State of the Artcited by 43
- 2022Towards Automated Document Revision: Grammatical Error Correction, Fluency Edits, and Beyondcited by 20
- 2021SMURF: SeMantic and linguistic UndeRstanding Fusion for Caption Evaluation via Typicality Analysiscited by 18
- 2021ComSum: Commit Messages Summarization and Meaning Preservationcited by 3
- 2024Revisiting Meta-evaluation for Grammatical Error Correctioncited by 3
- 2025Exploring the Feasibility of Multilingual Grammatical Error Correction with a Single LLM up to 9B parameters: A Comparative Study of 17 Modelscited by 2
- 2023MuLER: Detailed and Scalable Reference-based Evaluationcited by 0
- 2026Don't Count the Edits, Judge by the Outcome Alone: Reward-Based Evaluation for Grammatical Error Correctioncited by 0
- 2026Don't Count the Edits, Judge by the Outcome Alone: Reward-Based Evaluation for Grammatical Error Correction14 Sep 2026
- 2025Exploring the Feasibility of Multilingual Grammatical Error Correction with a Single LLM up to 9B parameters: A Comparative Study of 17 Models9 May 2025
- 2024Revisiting Meta-evaluation for Grammatical Error Correction5 Mar 2024
- 2023Efficient Benchmarking of Language Models22 Aug 2023
- 2023MuLER: Detailed and Scalable Reference-based Evaluation24 May 2023
- 2022Grammatical Error Correction: A Survey of the State of the Art9 Nov 2022
- 2022Towards Automated Document Revision: Grammatical Error Correction, Fluency Edits, and Beyond23 May 2022
- 2021ComSum: Commit Messages Summarization and Meaning Preservation23 Aug 2021
- 2021SMURF: SeMantic and linguistic UndeRstanding Fusion for Caption Evaluation via Typicality Analysis2 Jun 2021