Strong and Light Baseline Models for Fact-Checking Joint Inference
Kateryna Tymoshenko, Alessandro Moschitti · 2021
How to combine several pieces of evidence to verify a claim is an interesting semantic task.Very complex methods have been proposed, combining different evidence vectors using an evidence interaction graph.In this paper, we show that in case of inference based on transformer models, two effective approaches use either (i) a simple application of max pooling over the Transformer evidence vectors; or (ii) computing a weighted sum of the evidence vectors.Our experiments on the FEVER claim verification task show that the methods above achieve the state of the art, constituting strong baseline for much more computationally complex methods.