Papers with adversarial component
Adversarial Removal of Demographic Attributes from Text Data (D18-1)
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| Challenge: | Recent advances in Representation Learning and Adversarial Training remove unwanted features from the learned representation. |
| Approach: | They show that demographic information of authors is encoded in the intermediate representations learned by text-based neural classifiers. |
| Outcome: | The proposed approach achieves higher accuracies on the same dataset, the authors show . they show that the proposed approach is effective in removing unwanted features from the learned representations. |
Adversarial Propagation and Zero-Shot Cross-Lingual Transfer of Word Vector Specialization (D18-1)
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| Challenge: | Semantic specialization is a process of fine-tuning pre-trained distributional word vectors using external lexical knowledge to accentuate a particular semantic relation in the specialized vector space. |
| Approach: | They propose a method for specializing distributional word vectors using external lexical knowledge. |
| Outcome: | The proposed method improves on word similarity, dialog state tracking, and lexical simplification across three languages and on three tasks. |
Adversarial Training for Satire Detection: Controlling for Confounding Variables (N19-1)
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| Challenge: | Existing methods for satire detection focus on satirical news based on article sources . satiric news are written with the aim of mimicking regular news in diction . |
| Approach: | They propose a model for satire detection with an adversarial component to control for the confounding variable of publication source. |
| Outcome: | The proposed model improves generalization performance to unseen publications with an adversarial component. |