CLFEC: A New Task for Unified Linguistic and Factual Error Correction in paragraph-level Chinese Professional Writing
arXiv:2602.23845v2 Announce Type: replace Abstract: Chinese text correction has traditionally focused on spelling and grammar, while factual error correction is usually treated separately. However, in paragraph-level Chinese professional writing, linguistic (word/grammar/punctuation) and factual errors frequently co-occur and interact, while many draft-level errors are sparsely observable in published texts after editorial review, making unified correction both necessary and controlled benchmark construction essential. This paper introduces CLFEC (Chinese Linguistic \& Factual Error Correction
The increasing sophistication of AI for language tasks highlights the remaining challenge of integrating factual correctness with linguistic accuracy, especially in complex, professional texts.
This development addresses a critical gap in AI's ability to ensure both linguistic fluency and factual integrity in high-stakes documents, which is essential for automation in professional fields.
A new task and benchmark for combined linguistic and factual error correction in Chinese professional writing is introduced, providing a unified evaluation for a more holistic AI correction system.
- · AI text correction developers
- · Chinese professional writing platforms
- · Industries requiring high-accuracy document generation
- · Platforms offering only separate linguistic or factual correction
Improved AI systems capable of more comprehensive error correction in Chinese professional documents will emerge.
The methodology could be extended to other languages and professional domains, enhancing global AI-assisted content creation.
This could lead to a reduction in human editorial oversight for certain types of professional content, impacting related industries.
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Read at arXiv cs.CL