Papers by Franziska Zimmermann

1 papers
KnowMAN: Weakly Supervised Multinomial Adversarial Networks (2021.emnlp-main)

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Challenge: Existing approaches to weakly supervised training lack labeled data . weakly-supervised training can result in heuristic but noisy labels .
Approach: They propose a scheme that allows to control influence of signals associated with specific labeling functions.
Outcome: The proposed scheme improves results compared to weakly supervised learning with a pre-trained transformer language model and a feature-based baseline.

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