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ChatGPT vs. Grammarly? (arxiv.org)
10 points by sahin on Mar 27, 2023 | hide | past | pdf | 3 comments on HN

In plain words: ChatGPT was tested on a grammar-error correction set against Grammarly and specialist tools. It scored lower on automatic checks, especially on long sentences, because it rewrites phrases instead of fixing errors one by one; raters found fewer missed or wrong fixes but more over-corrections.

Abstract · ChatGPT or Grammarly? Evaluating ChatGPT on Grammatical Error Correction Benchmark

ChatGPT is a cutting-edge artificial intelligence language model developed by OpenAI, which has attracted a lot of attention due to its surprisingly strong ability in answering follow-up questions. In this report, we aim to evaluate ChatGPT on the Grammatical Error Correction(GEC) task, and compare it with commercial GEC product (e.g., Grammarly) and state-of-the-art models (e.g., GECToR). By testing on the CoNLL2014 benchmark dataset, we find that ChatGPT performs not as well as those baselines in terms of the automatic evaluation metrics (e.g., $F_{0.5}$ score), particularly on long sentences. We inspect the outputs and find that ChatGPT goes beyond one-by-one corrections. Specifically, it prefers to change the surface expression of certain phrases or sentence structure while maintaining grammatical correctness. Human evaluation quantitatively confirms this and suggests that ChatGPT produces less under-correction or mis-correction issues but more over-corrections. These results demonstrate that ChatGPT is severely under-estimated by the automatic evaluation metrics and could be a promising tool for GEC.

Haoran Wu, Wenxuan Wang, Yuxuan Wan, Wenxiang Jiao, Michael Lyu
arXiv:2303.13648 · cs.CL · submitted Mar 15, 2023
abstract · pdf · html · Working in progress

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Interesting how ChatGPT had a vastly higher tendency to "overcorrect" sentences (relative to Grammarly and GECToR), completely changing sentence structures to produce proper sentences rather than fixing specific grammar mistakes.

I wonder how the results of this study would have differed if the team looked at GPT-4?

It seems they used the web UI to do this. I wonder how it would have been if they did use the API and changed some parameters to reduce this modification effect.

honestly, seems like a paper without sufficient rigor

Would love to see the differences vs the Language Tool offering.