91 citations · 104 across the 12 of their papers we have counts for
4 papers · 1 filter
SepLL: Separating Latent Class Labels from Weak Supervision Noise
Andreas Stephan, Vasiliki Kougia, Benjamin Roth
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 f…
Topic Segmentation of Research Article Collections
Erion Çano, Benjamin Roth
Collections of research article data harvested from the web have become common recently since they are important resources for experimenting on tasks such as named entity recogniti…
Is the Computation of Abstract Sameness Relations Human-Like in Neural Language Models?
Lukas Thoma, Benjamin Roth
In recent years, deep neural language models have made strong progress in various NLP tasks. This work explores one facet of the question whether state-of-the-art NLP models exhibi…
WeaNF: Weak Supervision with Normalizing Flows
Andreas Stephan, Benjamin Roth
A popular approach to decrease the need for costly manual annotation of large data sets is weak supervision, which introduces problems of noisy labels, coverage and bias. Methods f…