Papers by Xincheng Ju

2 papers
Joint Multi-modal Aspect-Sentiment Analysis with Auxiliary Cross-modal Relation Detection (2021.emnlp-main)

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Challenge: Existing studies on aspect-level sentiment analysis focus on extracting aspect terms and sentiment polarities separately.
Approach: They propose a multi-modal joint learning approach with auxiliary cross-modal relation detection for multi-dimensional aspect-level sentiment analysis.
Outcome: The proposed approach can obtain all aspect-level sentiment polarities dependent on the jointly extracted specific aspects.
Multi-modal Multi-label Emotion Detection with Modality and Label Dependence (2020.emnlp-main)

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Challenge: Existing studies on multi-label emotion detection focus on one modality . current studies focus on label dependence, but there is no consensus on the model .
Approach: They propose a multi-modal sequence-to-set approach to model label dependence and modality dependence in a multiple-modal scenario.
Outcome: The proposed approach is able to model the label dependence and the modality dependence in a multi-modal scenario.

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