Papers with ANS

1 papers
Open World Classification with Adaptive Negative Samples (2022.emnlp-main)

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Challenge: Existing models with no effective open category data during training are limited by the lack of effective open categories data during the training stage.
Approach: They propose an approach to generate effective open category samples in the training stage and without requiring prior knowledge or external datasets.
Outcome: The proposed approach generates effective synthetic open category samples in the training stage and without requiring any prior knowledge or external datasets.

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