52 citations · 73 across the 16 of their papers we have counts for
17 papers
IndicSafeEval: Safety Robustness of Large Language Models under Multilingual Persuasive Jailbreak Attacks
Saikat Mondal, Mamta, Deeksha Varshney +2
Large language models (LLMs) are increasingly used in multilingual settings, yet their safety is still evaluated primarily in English. This limits our understanding of how alignmen…
Key Point Analysis Needs Structure Recovery: Task Definition, Dataset Diagnosis, and a Structure-Aware Benchmark
Zhiqiang Shi, Oana Cocarascu
Key Point Analysis (KPA) aims to identify a concise set of key points that summarize a collection of arguments together with their prevalence. We argue that KPA is fundamentally a…
MLingualFC: Evaluating Jailbreak Vulnerabilities in Multilingual Vision-Language Models
Rishabh Makwana, Mamta, Deeksha Varshney +1
Vision-Language Models (VLMs) have demonstrated strong performance across multimodal tasks, yet their safety robustness remains an open challenge. While prior work has shown that s…
The Automated Verification of Textual Claims (AVeriTeC) Shared Task
Michael Schlichtkrull, Yulong Chen, Chenxi Whitehouse +9
The Automated Verification of Textual Claims (AVeriTeC) shared task asks participants to retrieve evidence and predict veracity for real-world claims checked by fact-checkers. Evid…
Argumentation and Machine Learning
Antonio Rago, Kristijonas Čyras, Jack Mumford +1
This chapter provides an overview of research works that present approaches with some degree of cross-fertilisation between Computational Argumentation and Machine Learning. Our re…
Towards Dialogues for Joint Human-AI Reasoning and Value Alignment
Elfia Bezou-Vrakatseli, Oana Cocarascu, Sanjay Modgil
We argue that enabling human-AI dialogue, purposed to support joint reasoning (i.e., 'inquiry'), is important for ensuring that AI decision making is aligned with human values and…
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…
FEVEROUS: Fact Extraction and VERification Over Unstructured and Structured information
Rami Aly, Zhijiang Guo, Michael Schlichtkrull +5
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…
An Explanatory Query-Based Framework for Exploring Academic Expertise
Oana Cocarascu, Andrew McLean, Paul French +1
The success of research institutions heavily relies upon identifying the right researchers "for the job": researchers may need to identify appropriate collaborators, often from acr…
Automatic Product Ontology Extraction from Textual Reviews
Joel Oksanen, Oana Cocarascu, Francesca Toni
Ontologies have proven beneficial in different settings that make use of textual reviews. However, manually constructing ontologies is a laborious and time-consuming process in nee…
A Dataset Independent Set of Baselines for Relation Prediction in Argument Mining
Oana Cocarascu, Elena Cabrio, Serena Villata +1
Argument Mining is the research area which aims at extracting argument components and predicting argumentative relations (i.e.,support and attack) from text. In particular, numerou…
The Fact Extraction and VERification (FEVER) Shared Task
James Thorne, Andreas Vlachos, Oana Cocarascu +2
We present the results of the first Fact Extraction and VERification (FEVER) Shared Task. The task challenged participants to classify whether human-written factoid claims could be…