52 citations · 73 across the 16 of their papers we have counts for
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Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular Data
Mubashara Akhtar, Abhilash Shankarampeta, Vivek Gupta +3
Numbers are crucial for various real-world domains such as finance, economics, and science. Thus, understanding and reasoning with numbers are essential skills for language models…
ChartCheck: Explainable Fact-Checking over Real-World Chart Images
Mubashara Akhtar, Nikesh Subedi, Vivek Gupta +3
Whilst fact verification has attracted substantial interest in the natural language processing community, verifying misinforming statements against data visualizations such as char…
Identifying Reasons for Bias: An Argumentation-Based Approach
Madeleine Waller, Odinaldo Rodrigues, Oana Cocarascu
As algorithmic decision-making systems become more prevalent in society, ensuring the fairness of these systems is becoming increasingly important. Whilst there has been substantia…
Bias Mitigation Methods for Binary Classification Decision-Making Systems: Survey and Recommendations
Madeleine Waller, Odinaldo Rodrigues, Oana Cocarascu
Bias mitigation methods for binary classification decision-making systems have been widely researched due to the ever-growing importance of designing fair machine learning processe…
Multimodal Automated Fact-Checking: A Survey
Mubashara Akhtar, Michael Schlichtkrull, Zhijiang Guo +3
Misinformation is often conveyed in multiple modalities, e.g. a miscaptioned image. Multimodal misinformation is perceived as more credible by humans, and spreads faster than its t…
Reading and Reasoning over Chart Images for Evidence-based Automated Fact-Checking
Mubashara Akhtar, Oana Cocarascu, Elena Simperl
Evidence data for automated fact-checking (AFC) can be in multiple modalities such as text, tables, images, audio, or video. While there is increasing interest in using images for…