Papers by Xiaochen Zhou

2 papers
Graph Ensemble Learning over Multiple Dependency Trees for Aspect-level Sentiment Classification (2021.naacl-main)

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Challenge: Recent work on aspect-level sentiment classification has shown that syntactic information is effective in capturing long-range syntaktic relations that are obscure from the surface form.
Approach: They propose a graph ensemble technique that integrates syntactic structures with GNNs to better leverage syntaktic information in the face of parsing errors.
Outcome: The proposed model outperforms models with single dependency tree and beats other models without adding model parameters.
Personality Understanding of Fictional Characters during Book Reading (2023.acl-long)

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Challenge: Existing methods to predict characters' personalities have not been studied in the NLP field due to the lack of appropriate datasets mimicking the process of book reading.
Approach: They propose a dataset to predict characters' personalities that uses an exhaustive vocabulary of personality traits as targets.
Outcome: The proposed dataset is efficient and accurate and relies on long-term context to achieve accurate predictions for both machines and humans.

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