Papers by Wenxin Hou

1 papers
Exploiting Unlabeled Data for Target-Oriented Opinion Words Extraction (2022.coling-1)

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Challenge: Existing methods to extract opinion words from sentences are limited due to the expensive annotation process.
Approach: They propose to exploit massive unlabeled data to reduce distribution shift risk . they propose to use two filters specifically for TOWE to filter noisy data . results indicate superiority of MGCR over current state-of-the-art methods .
Outcome: The proposed method reduces the risk of distribution shifts by increasing the exposure of the model to varying distribution shift.

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