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Andreas Stephan

3 accepted papers

2023

Weaker Than You Think: A Critical Look at Weakly Supervised Learning

ACL 2023long

Weakly supervised learning is a popular approach for training machine learning models in low-resource settings. Instead of requesting high-quality yet costly human annotations, it allows training models with noisy annotations obtained from various weak sources. Recently, many sophisticated approache…

2022

SepLL: Separating Latent Class Labels from Weak Supervision Noise

EMNLP 2022finding

In the weakly supervised learning paradigm, labeling functions automatically assign heuristic, often noisy, labels to data samples. In this work, we provide a method for learning from weak labels by separating two types of complementary information associated with the labeling functions: information…