Papers by Jianwang Wu

2 papers
Enhancing Language Representation with Constructional Information for Natural Language Understanding (2023.acl-long)

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Challenge: Recent advances in natural language processing focus on acquiring lexico-semantic information.
Approach: They propose a construction grammar which highlights the pairings of form and meaning to enrich language representation.
Outcome: The proposed model is superior to existing models on a variety of NLU tasks.
FCGEC: Fine-Grained Corpus for Chinese Grammatical Error Correction (2022.findings-emnlp)

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Challenge: grammatical error correction (GEC) is a complex task that requires high-quality data from native speakers.
Approach: They propose a human-annotated corpus to detect, identify and correct grammatical errors in Chinese examinations.
Outcome: The proposed model outperforms other models in low-resource settings, but there is a significant gap between the models and humans that encourages future models to bridge it.

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