29 citations · 145 across the 25 of their papers we have counts for
8 papers · 1 filter
Encoding word order in complex embeddings
Benyou Wang, Donghao Zhao, Christina Lioma +3
Sequential word order is important when processing text. Currently, neural networks (NNs) address this by modeling word position using position embeddings. The problem is that posi…
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…
Contextually Propagated Term Weights for Document Representation
Casper Hansen, Christian Hansen, Stephen Alstrup +2
Word embeddings predict a word from its neighbours by learning small, dense embedding vectors. In practice, this prediction corresponds to a semantic score given to the predicted w…
Unsupervised Neural Generative Semantic Hashing
Casper Hansen, Christian Hansen, Jakob Grue Simonsen +2
Fast similarity search is a key component in large-scale information retrieval, where semantic hashing has become a popular strategy for representing documents as binary hash codes…
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…
Modelling Sequential Music Track Skips using a Multi-RNN Approach
Christian Hansen, Casper Hansen, Stephen Alstrup +2
Modelling sequential music skips provides streaming companies the ability to better understand the needs of the user base, resulting in a better user experience by reducing the nee…