51 citations · 118 across the 35 of their papers we have counts for
3 papers · 1 filter
Feature-Dependent Confusion Matrices for Low-Resource NER Labeling with Noisy Labels
Lukas Lange, Michael A. Hedderich, Dietrich Klakow
In low-resource settings, the performance of supervised labeling models can be improved with automatically annotated or distantly supervised data, which is cheap to create but ofte…
Using Multi-Sense Vector Embeddings for Reverse Dictionaries
Michael A. Hedderich, Andrew Yates, Dietrich Klakow +1
Popular word embedding methods such as word2vec and GloVe assign a single vector representation to each word, even if a word has multiple distinct meanings. Multi-sense embeddings…
Handling Noisy Labels for Robustly Learning from Self-Training Data for Low-Resource Sequence Labeling
Debjit Paul, Mittul Singh, Michael A. Hedderich +1
In this paper, we address the problem of effectively self-training neural networks in a low-resource setting. Self-training is frequently used to automatically increase the amount…