Papers with seed-based distance metrics

1 papers
Progressive Adversarial Learning for Bootstrapping: A Case Study on Entity Set Expansion (2021.emnlp-main)

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Challenge: Existing methods for entity set expansion define the expansion boundary using seed-based distance metrics, which are hard to adjust due to the extremely sparse supervision.
Approach: They propose a new learning method for bootstrapping which jointly models the bootstraping process and boundary learning process in a GAN framework.
Outcome: The proposed method achieves the new state-of-the-art performance for entity set expansion.

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