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    Adaptive Feature Discrimination and Denoising for Asymmetric Text Matching (2022.coling-1)

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    Challenge: Existing models focus on asymmetric text matching but rarely perform feature denoising . existing models focus only on recognizing discriminative features and filtering out irrelevant features .
    Approach: They propose a novel adaptive feature discrimination and denoising model for asymmetric text matching . it explicitly distinguishes discriminative features and filters out irrelevant features in context .
    Outcome: The proposed model achieves significant performance gains over current state-of-the-art models on four real-world datasets.

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