Litcius/Paper detail

Verdict Inference with Claim and Retrieved Elements Using RoBERTa

In-Zu Gi, Ting-Yu Fang, Richard Tzong‐Han Tsai

202110 citationsDOIOpen Access PDF

Abstract

Automatic fact verification has attracted recent research attention as the increasing dissemination of disinformation on social media platforms. The FEVEROUS shared task introduces a benchmark for fact verification, in which a system is challenged to verify the given claim using the extracted evidential elements from Wikipedia documents. In this paper, we propose our 3 rd place three-stage system consisting of document retrieval, element retrieval, and verdict inference for the FEVER-OUS shared task. By considering the context relevance in the fact extraction and verification task, our system achieves 0.29 FEVER-OUS score on the development set and 0.25 FEVEROUS score on the blind test set, both outperforming the FEVEROUS baseline.

Topics & Concepts

Computer scienceVerdictContext (archaeology)InferenceBenchmark (surveying)DisinformationTask (project management)Relevance (law)Set (abstract data type)Baseline (sea)Information retrievalTest setArtificial intelligenceNatural language processingMachine learningData miningSocial mediaWorld Wide WebProgramming languageEngineeringLawGeographyBiologyPaleontologyGeodesySystems engineeringPolitical scienceTopic ModelingNatural Language Processing TechniquesMisinformation and Its Impacts