Papers by Zuocheng Li

1 papers
t-HNE: A Text-guided Hierarchical Noise Eliminator for Multimodal Sentiment Analysis (2025.coling-main)

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Challenge: Existing methods for multimodal sentiment analysis assume that all modalities contribute equally to model performance.
Approach: They propose a text-guided Hierarchical Noise Eliminator model that extracts modality-consistent information from unimodal data and integrates it into multimodal representations for sentiment classification.
Outcome: The proposed model reduces noise caused by modality inconsistency by maximizing mutual information between textual representations and visual and acoustic representations.

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