Abstract Grammatical Error Correction (GEC) is the task of automatically detecting and
correcting errors in text. The task not only includes the correction of grammatical errors, such …

To mitigate the high inference latency stemming from autoregressive decoding in Large
Language Models (LLMs), Speculative Decoding has emerged as a novel decoding …

Advancements in deep neural networks have allowed automatic speech recognition (ASR)
systems to attain human parity on several publicly available clean speech datasets …

This paper presents MuCGEC, a multi-reference multi-source evaluation dataset for Chinese
Grammatical Error Correction (CGEC), consisting of 7,063 sentences collected from three …

Recent advances in the capacity of large language models to generate human-like text have
resulted in their increased adoption in user-facing settings. In parallel, these improvements …

Grammatical error correction (GEC) can be divided into sequence-to-edit (Seq2Edit) and
sequence-to-sequence (Seq2Seq) frameworks, both of which have their pros and cons. To …

This work proposes a syntax-enhanced grammatical error correction (GEC) approach
named SynGEC that effectively incorporates dependency syntactic information into the …

Grammatical error correction (GEC) is one of the major tasks in natural language processing
(NLP) which has recently attracted great attention from researchers. The performance of …

State-of-the-art chatbots for English are now able to hold conversations on virtually any topic
(eg Adiwardana et al., 2020; Roller et al., 2021). However, existing dialogue systems in the …

Grammatical error correction tools are effective at correcting grammatical errors in users'
input sentences but do not provide users with\textit {natural language} explanations about …