91 citations · 99 across the 4 of their papers we have counts for
5 papers
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word embeddings using positive pointwise mutual information (PPMI) weighted co-occurrence matrices have been widely superseded by machine-learning-b…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…
Domain adaptation for part-of-speech tagging of noisy user-generated text
Luisa März, Dietrich Trautmann, Benjamin Roth
The performance of a Part-of-speech (POS) tagger is highly dependent on the domain ofthe processed text, and for many domains there is no or only very little training data availabl…
Comparing Convolutional Neural Networks to Traditional Models for Slot Filling
Heike Adel, Benjamin Roth, Hinrich Schütze
We address relation classification in the context of slot filling, the task of finding and evaluating fillers like "Steve Jobs" for the slot X in "X founded Apple". We propose a co…
Compositional Vector Space Models for Knowledge Base Completion
Arvind Neelakantan, Benjamin Roth, Andrew McCallum
Knowledge base (KB) completion adds new facts to a KB by making inferences from existing facts, for example by inferring with high likelihood nationality(X,Y) from bornIn(X,Y). Mos…