Papers by Yijie Lin

2 papers
Improve Interpretability of Neural Networks via Sparse Contrastive Coding (2022.findings-emnlp)

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Challenge: XAI has achieved remarkable advances, but few efforts have been devoted to solving the problem.
Approach: They propose a model-agnostic explanation method termed Sparse Contrastive Coding . they use model-based explanations to explain the black-box in a more model-oriented way .
Outcome: The proposed method outperforms five state-of-the-art methods in interpretability and classification metrics.
Multimodal Transformers are Hierarchical Modal-wise Heterogeneous Graphs (2025.acl-long)

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Challenge: Multimodal Sentiment Analysis (MSA) is a rapidly developing field that integrates multimodal information to recognize sentiments.
Approach: They propose a multimodal fusion model that integrates multimodal information to recognize sentiments using multimodal transformers.
Outcome: The proposed model achieves significantly higher performance than MulTs and the existing model is robust.

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