Papers with GEC methods

2 papers
Explanation based In-Context Demonstrations Retrieval for Multilingual Grammatical Error Correction (2025.naacl-long)

Copied to clipboard

Challenge: Grammatical error correction (GEC) aims to correct grammatical, spelling, and semantic errors in natural language text.
Approach: They propose a retrieval method based on natural language grammatical error explanations to match inputs with pre-constructed databases where explanations for erroneous samples are generated by LLMs.
Outcome: The proposed method outperforms existing semantic and BM25-based retrieval techniques without additional training or language adaptation.
CxGGEC: Construction-Guided Grammatical Error Correction (2025.acl-long)

Copied to clipboard

Challenge: Current GEC methods rely on grammatical labels for syntactic information, often overlooking the inherent usage patterns of language.
Approach: They propose to use construction grammar to capture underlying language patterns and guide corrections by decoding construction tokens into their original forms and correcting erroneous tokens.
Outcome: The proposed model captures underlying language patterns and corrects erroneous construction tokens on English and Chinese benchmarks.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations