This research pioneers the use of fine-tuned Large Language Models (LLMs) to automate
Systematic Literature Reviews (SLRs), presenting a significant and novel contribution in …

Fact-checking is an essential tool to mitigate the spread of misinformation and
disinformation. We introduce the task of fact-checking in dialogue, which is a relatively …

We introduce a new benchmark, COVID-VTS, for fact-checking multi-modal information
involving short-duration videos with COVID19-focused information from both the real world …

The task of fact-checking deals with assessing the veracity of factual claims based on
credible evidence and background knowledge. In particular, scientific fact-checking is the …

Natural Language Inference (NLI) has been extensively studied by the NLP community as a
framework for estimating the semantic relation between sentence pairs. While early work …

Large language models (LMs) are prone to generate diverse factually incorrect statements,
which are widely called hallucinations. Current approaches predominantly focus on coarse …

When searching the web for answers to health questions, people can make incorrect
decisions that have a negative effect on their lives if the search results contain …

Automated claim checking is the task of determining the veracity of a claim given evidence
retrieved from a textual knowledge base of trustworthy facts. While previous work has taken …

The large and ever-increasing amount of data available on the Internet coupled with the
laborious task of manual claim and fact verification has sparked the interest in the …

The commonsense natural language inference (CNLI) tasks aim to select the most likely
follow-up statement to a contextual description of ordinary, everyday events and facts …