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- W4287639788 abstract "Evaluation of grammatical error correction (GEC) systems has primarily focused on essays written by non-native learners of English, which however is only part of the full spectrum of GEC applications. We aim to broaden the target domain of GEC and release CWEB, a new benchmark for GEC consisting of website text generated by English speakers of varying levels of proficiency. Website data is a common and important domain that contains far fewer grammatical errors than learner essays, which we show presents a challenge to state-of-the-art GEC systems. We demonstrate that a factor behind this is the inability of systems to rely on a strong internal language model in low error density domains. We hope this work shall facilitate the development of open-domain GEC models that generalize to different topics and genres." @default.
- W4287639788 created "2022-07-25" @default.
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- W4287639788 date "2020-10-15" @default.
- W4287639788 modified "2023-09-29" @default.
- W4287639788 title "Grammatical Error Correction in Low Error Density Domains: A New Benchmark and Analyses" @default.
- W4287639788 doi "https://doi.org/10.48550/arxiv.2010.07574" @default.
- W4287639788 hasPublicationYear "2020" @default.
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