Papers by Qingting Xu

4 papers
Low-Resource Comparative Opinion Quintuple Extraction by Data Augmentation with Prompting (2023.findings-emnlp)

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Challenge: Comparative Opinion Quintuple Extraction (COQE) aims to predict comparative opinion quintuples from comparative sentences.
Approach: They propose a low-resource approach to extract comparative opinion quintuples from comparative sentences . they propose augmentation using ChatGPT and a data-centric approach .
Outcome: The proposed approach improves the existing pipeline-based method and achieves state-of-the-art results.
Word-level Commonsense Knowledge Selection for Event Detection (2024.lrec-main)

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Challenge: Event Detection (ED) is a task of automatically extracting multi-class trigger words . Xie and Tu, 2022, use a Context-specific Knowledge Selector to select commonsense knowledge of words based on living contexts .
Approach: They use a Context-specific Knowledge Selector to select the exact commonsense knowledge of words from a large knowledge base.
Outcome: The proposed approach achieves the F1-score of about 78.3% on the ACE-2005 dataset.
Smart “Chef”: Verifying the Effect of Role-based Paraphrasing for Aspect Term Extraction (2023.findings-emnlp)

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Challenge: Aspect Term Extraction (ATE) is a task of automatically extracting aspect terms from sentences.
Approach: They propose to automatically rewrite sentences from virtual experts with different roles . they leverage ChatGPT to determine virtual experts in the considered domains .
Outcome: The proposed method can be used to expand the predictions obtained on the original sentences without retraining or fine-tuning the baseline extractors.
COF: Adaptive Chain of Feedback for Comparative Opinion Quintuple Extraction (2025.coling-main)

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Challenge: Comparative Opinion Quintuple Extraction (COQE) aims to extract all comparative sentiment quintuples from product review text.
Approach: They propose a model-unaware adaptive chain-of-feedback method to extract quintuples from product review text.
Outcome: The proposed method improves performance on three benchmarks.

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