29 citations · 145 across the 25 of their papers we have counts for
9 papers · 1 filter
Language Modeling Using Tensor Trains
Zhan Su, Yuqin Zhou, Fengran Mo +1
We propose a novel tensor network language model based on the simplest tensor network (i.e., tensor trains), called `Tensor Train Language Model' (TTLM). TTLM represents sentences…
Fact Checking with Insufficient Evidence
Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma +1
Automating the fact checking (FC) process relies on information obtained from external sources. In this work, we posit that it is crucial for FC models to make veracity predictions…
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…
A Diagnostic Study of Explainability Techniques for Text Classification
Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma +1
Recent developments in machine learning have introduced models that approach human performance at the cost of increased architectural complexity. Efforts to make the rationales beh…
Generating Fact Checking Explanations
Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma +1
Most existing work on automated fact checking is concerned with predicting the veracity of claims based on metadata, social network spread, language used in claims, and, more recen…
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…