Combining sentence and table evidence to predict veracity of factual claims using TaPaS and RoBERTa
Martin Funkquist · 2021
This paper describes a method for retrieving evidence and predicting the veracity of factual claims, on the FEVEROUS dataset.The evidence consists of both sentences and table cells.The proposed method is part of the FEVER shared task.It uses similarity scores between TF-IDF vectors to retrieve the textual evidence and similarity scores between dense vectors created by fine-tuned TaPaS models for tabular evidence retrieval.The evidence is passed through a dense neural network, that is trained on the FEVEROUS dataset, to produce a veracity label.The FEVEROUS score for the proposed model is 0.126 on the test dataset.