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publications
Leveraging Denoised Abstract Meaning Representation for Grammatical Error Correction
Published in ACL 2023, pages 7180–7188, 2023
In this paper, we propose the AMR-GEC, a seq-to-seq model that incorporates denoised AMR as additional knowledge. Specifically, We design a semantic aggregated GEC model and explore denoising methods to get AMRs more reliable. Experiments on the BEA-2019 shared task and the CoNLL-2014 shared task have shown that AMR-GEC performs comparably to a set of strong baselines with a large number of synthetic data.
Recommended citation: Hejing Cao and Dongyan Zhao. 2023. Leveraging Denoised Abstract Meaning Representation for Grammatical Error Correction. In Findings of the Association for Computational Linguistics: ACL 2023, pages 7180–7188, Toronto, Canada. Association for Computational Linguistics. https://aclanthology.org/2023.findings-acl.449/
teaching
Introduction to Computation (B), (Teaching Assistant)
Undergraduate course, School of Electronic Engineering and Computer Science, Peking University, 2021
Introduction to Computation (B), (Teaching Assistant)
Undergraduate course, School of Electronic Engineering and Computer Science, Peking University, 2022