91 citations · 104 across the 12 of their papers we have counts for
15 papers · 1 filter
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…
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…
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…
Dirichlet-Smoothed Word Embeddings for Low-Resource Settings
Jakob Jungmaier, Nora Kassner, Benjamin Roth
Nowadays, classical count-based word embeddings using positive pointwise mutual information (PPMI) weighted co-occurrence matrices have been widely superseded by machine-learning-b…
Interpretable Question Answering on Knowledge Bases and Text
Alona Sydorova, Nina Poerner, Benjamin Roth
Interpretability of machine learning (ML) models becomes more relevant with their increasing adoption. In this work, we address the interpretability of ML based question answering…