91 citations · 104 across the 12 of their papers we have counts for
6 papers · 1 filter
Focused Contrastive Training for Test-based Constituency Analysis
Benjamin Roth, Erion Çano
We propose a scheme for self-training of grammaticality models for constituency analysis based on linguistic tests. A pre-trained language model is fine-tuned by contrastive estima…
KnowMAN: Weakly Supervised Multinomial Adversarial Networks
Luisa März, Ehsaneddin Asgari, Fabienne Braune +2
The absence of labeled data for training neural models is often addressed by leveraging knowledge about the specific task, resulting in heuristic but noisy labels. The knowledge is…
Proceedings of the First Workshop on Weakly Supervised Learning (WeaSuL)
Michael A. Hedderich, Benjamin Roth, Katharina Kann +3
Welcome to WeaSuL 2021, the First Workshop on Weakly Supervised Learning, co-located with ICLR 2021. In this workshop, we want to advance theory, methods and tools for allowing exp…
Data Centric Domain Adaptation for Historical Text with OCR Errors
Luisa März, Stefan Schweter, Nina Poerner +2
We propose new methods for in-domain and cross-domain Named Entity Recognition (NER) on historical data for Dutch and French. For the cross-domain case, we address domain shift by…
Knodle: Modular Weakly Supervised Learning with PyTorch
Anastasiia Sedova, Andreas Stephan, Marina Speranskaya +1
Strategies for improving the training and prediction quality of weakly supervised machine learning models vary in how much they are tailored to a specific task or integrated with a…
Ranking vs. Classifying: Measuring Knowledge Base Completion Quality
Marina Speranskaya, Martin Schmitt, Benjamin Roth
Knowledge base completion (KBC) methods aim at inferring missing facts from the information present in a knowledge base (KB) by estimating the likelihood of candidate facts. In the…