Claim veracity detection aims to automatically infer the veracity of a given claim based on relevant evidence retrieved from multiple documents. Work carried out in our group includes fact checking, multimodal fake news detection, and COVID-related claim veracity detection.
Miguel Arana Catania, Lin Gui, John Dougrez-Lewis, Wenjia Zhang, Runcong Zhao
- M. Arana Catania, E. Kochkina, A. Zubiaga, M. Liakata, R. Procter and Y. He. Natural Language Inference with Self-Attention for Veracity Assessment of Pandemic Claims. 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), Jul. 2022. [dataset]
J. Dougrez-Lewis, M. Arana Catania, E. Kochkina, M. Liakata and Y. He. PHEMEPlus: Enriching Social Media Rumour Verification with External Evidence. The 5th FEVER Workshop, co-located with ACL, May 2022.
- Zhang, L. Gui and Y. He. Supervised Contrastive Learning for Multi-modal Unreliable News Detection in COVID-19 Pandemic, The 30th ACM International Conference on Information and Knowledge Management (CIKM), Nov. 2021.
- J. Si, D. Zhou, T. Li, X. Shi and Y. He. Topic-aware Evidence Reasoning and Stance-aware Aggregating for Fact Verification, The 59th Annual Meeting of the Association for Computational Linguistics (ACL), Aug. 2021.
- J. Dougrez-Lewis, E. Kochkina, M. Liakata and Y. He. Learning Disentangled Latent Topics for Twitter Rumour Veracity Classification, ACL Findings, 2021.