Feb. 8, 2024, 5:46 a.m. | Haihui Yang Xiaojun Quan

cs.CL updates on arXiv.org arxiv.org

Chinese grammatical error correction (CGEC) faces serious overcorrection challenges when employing autoregressive generative models such as sequence-to-sequence (Seq2Seq) models and decoder-only large language models (LLMs). While previous methods aim to address overcorrection in Seq2Seq models, they are difficult to adapt to decoder-only LLMs. In this paper, we propose an alignment-enhanced corrector for the overcorrection problem that applies to both Seq2Seq models and decoder-only LLMs. Our method first trains a correction model to generate an initial correction of the source sentence. …

adapt aim alignment challenges chinese cs.ai cs.cl decoder error error correction generative generative models language language models large language large language models llms paper seq2seq

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