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Tianxiang Wang

4 accepted papers

2025

CxGGEC: Construction-Guided Grammatical Error Correction

ACL 2025long

The grammatical error correction (GEC) task aims to detect and correct grammatical errors in text to enhance its accuracy and readability. Current GEC methods primarily rely on grammatical labels for syntactic information, often overlooking the inherent usage patterns of language. In this work, we e…

Cited by 0SourcePDFScholar
2024

CoELM: Construction-Enhanced Language Modeling

ACL 2024long

Recent studies have shown that integrating constructional information can improve the performance of pre-trained language models (PLMs) in natural language understanding. However, exploration into leveraging constructional information to enhance generative language models for natural language genera…

2023

Enhancing Language Representation with Constructional Information for Natural Language Understanding

ACL 2023long

Natural language understanding (NLU) is an essential branch of natural language processing, which relies on representations generated by pre-trained language models (PLMs). However, PLMs primarily focus on acquiring lexico-semantic information, while they may be unable to adequately handle the meani…

2023

Multi-Action Dialog Policy Learning from Logged User Feedback

AAAI 2023technical

Multi-action dialog policy (MADP), which generates multiple atomic dialog actions per turn, has been widely applied in task-oriented dialog systems to provide expressive and efficient system responses. Existing MADP models usually imitate action combinations from the labeled multi-action dialog samp…