Papers by Puli Chen

3 papers
Can ChatGPT’s Performance be Improved on Verb Metaphor Detection Tasks? Bootstrapping and Combining Tacit Knowledge (2024.acl-long)

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Challenge: Existing methods for supervised metaphor detection are limited by their performance.
Approach: They propose to use ChatGPT to detect most prevalent verb metaphors among metaphors . they use literal collocations of target verbs and subject-object pairs of verbs to detect them .
Outcome: The proposed method achieves the best performance on the unsupervised verb metaphors detection task compared to existing unsupervised methods or direct prediction using ChatGPT.
Merely Judging Metaphor is Not Enough: Research on Reasonable Metaphor Detection (2024.findings-emnlp)

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Challenge: Current metaphor detection tasks only provide labels without interpreting how to understand them.
Approach: They propose to improve the current metaphor detection task by using mainstream Large Language Models.
Outcome: The proposed model is based on the original sentence, target word, and usage . the model is then evaluated using manual evaluation .
DAGS: A Dependency-Based Dual-Attention and Global Semantic Improvement Framework for Metaphor Recognition (2025.findings-acl)

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Challenge: Existing methods for metaphor recognition ignore interference caused by literal annotations . et al., 2018: Metaphor recognition plays an important role in cognition and communication .
Approach: They propose a dependency-based Dual-Attention and Global Semantic Improvement framework to improve metaphor recognition.
Outcome: The proposed framework can extract features from multiple information sources while improving on mainstream metaphor datasets.

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