1 code implementation • 22 May 2023 • Mubashara Akhtar, Michael Schlichtkrull, Zhijiang Guo, Oana Cocarascu, Elena Simperl, Andreas Vlachos
In this survey, we conceptualise a framework for AFC including subtasks unique to multimodal misinformation.
1 code implementation • NeurIPS 2023 • Michael Schlichtkrull, Zhijiang Guo, Andreas Vlachos
Existing datasets for automated fact-checking have substantial limitations, such as relying on artificial claims, lacking annotations for evidence and intermediate reasoning, or including evidence published after the claim.
1 code implementation • 27 Apr 2023 • Michael Schlichtkrull, Nedjma Ousidhoum, Andreas Vlachos
Automated fact-checking is often presented as an epistemic tool that fact-checkers, social media consumers, and other stakeholders can use to fight misinformation.
1 code implementation • 26 Aug 2021 • Zhijiang Guo, Michael Schlichtkrull, Andreas Vlachos
Fact-checking has become increasingly important due to the speed with which both information and misinformation can spread in the modern media ecosystem.
1 code implementation • 10 Jun 2021 • Rami Aly, Zhijiang Guo, Michael Schlichtkrull, James Thorne, Andreas Vlachos, Christos Christodoulopoulos, Oana Cocarascu, Arpit Mittal
Fact verification has attracted a lot of attention in the machine learning and natural language processing communities, as it is one of the key methods for detecting misinformation.
no code implementations • 1 Jan 2021 • Sewon Min, Jordan Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih
We review the EfficientQA competition from NeurIPS 2020.
no code implementations • ACL 2021 • Michael Schlichtkrull, Vladimir Karpukhin, Barlas Oğuz, Mike Lewis, Wen-tau Yih, Sebastian Riedel
Structured information is an important knowledge source for automatic verification of factual claims.
1 code implementation • Findings (NAACL) 2022 • Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Schlichtkrull, Sonal Gupta, Yashar Mehdad, Scott Yih
We study open-domain question answering with structured, unstructured and semi-structured knowledge sources, including text, tables, lists and knowledge bases.
Ranked #1 on Open-Domain Question Answering on WebQuestions (using extra training data)
Knowledge Base Question Answering Open-Domain Question Answering
2 code implementations • EMNLP 2020 • Nicola De Cao, Michael Schlichtkrull, Wilker Aziz, Ivan Titov
Attribution methods assess the contribution of inputs to the model prediction.
1 code implementation • EACL 2017 • Michael Schlichtkrull, Anders S{\o}gaard
In cross-lingual dependency annotation projection, information is often lost during transfer because of early decoding.
27 code implementations • 17 Mar 2017 • Michael Schlichtkrull, Thomas N. Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, Max Welling
We demonstrate the effectiveness of R-GCNs as a stand-alone model for entity classification.
Ranked #1 on Node Classification on AIFB