41 citations · 47 across the 6 of their papers we have counts for
7 papers
Large Language Models are Few-Shot Training Example Generators: A Case Study in Fallacy Recognition
Tariq Alhindi, Smaranda Muresan, Preslav Nakov
Recognizing fallacies is crucial for ensuring the quality and validity of arguments across various domains. However, computational fallacy recognition faces challenges due to the d…
Multitask Instruction-based Prompting for Fallacy Recognition
Tariq Alhindi, Tuhin Chakrabarty, Elena Musi +1
Fallacies are used as seemingly valid arguments to support a position and persuade the audience about its validity. Recognizing fallacies is an intrinsically difficult task both fo…
AraStance: A Multi-Country and Multi-Domain Dataset of Arabic Stance Detection for Fact Checking
Tariq Alhindi, Amal Alabdulkarim, Ali Alshehri +2
With the continuing spread of misinformation and disinformation online, it is of increasing importance to develop combating mechanisms at scale in the form of automated systems tha…
"Sharks are not the threat humans are": Argument Component Segmentation in School Student Essays
Tariq Alhindi, Debanjan Ghosh
Argument mining is often addressed by a pipeline method where segmentation of text into argumentative units is conducted first and proceeded by an argument component identification…
Machine Generation and Detection of Arabic Manipulated and Fake News
El Moatez Billah Nagoudi, AbdelRahim Elmadany, Muhammad Abdul-Mageed +2
Fake news and deceptive machine-generated text are serious problems threatening modern societies, including in the Arab world. This motivates work on detecting false and manipulate…
DeSePtion: Dual Sequence Prediction and Adversarial Examples for Improved Fact-Checking
Christopher Hidey, Tuhin Chakrabarty, Tariq Alhindi +4
The increased focus on misinformation has spurred development of data and systems for detecting the veracity of a claim as well as retrieving authoritative evidence. The Fact Extra…