29 citations · 116 across the 14 of their papers we have counts for
5 papers · 1 filter
Automatic Fake News Detection: Are Models Learning to Reason?
Casper Hansen, Christian Hansen, Lucas Chaves Lima
Most fact checking models for automatic fake news detection are based on reasoning: given a claim with associated evidence, the models aim to estimate the claim veracity based on t…
Multi-Head Self-Attention with Role-Guided Masks
Dongsheng Wang, Casper Hansen, Lucas Chaves Lima +4
The state of the art in learning meaningful semantic representations of words is the Transformer model and its attention mechanisms. Simply put, the attention mechanisms learn to a…
MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims
Isabelle Augenstein, Christina Lioma, Dongsheng Wang +4
We contribute the largest publicly available dataset of naturally occurring factual claims for the purpose of automatic claim verification. It is collected from 26 fact checking we…
Neural Speed Reading with Structural-Jump-LSTM
Christian Hansen, Casper Hansen, Stephen Alstrup +2
Recurrent neural networks (RNNs) can model natural language by sequentially 'reading' input tokens and outputting a distributed representation of each token. Due to the sequential…
Predicting Distresses using Deep Learning of Text Segments in Annual Reports
Rastin Matin, Casper Hansen, Christian Hansen +1
Corporate distress models typically only employ the numerical financial variables in the firms' annual reports. We develop a model that employs the unstructured textual data in the…