13 citations · 24 across the 4 of their papers we have counts for
7 papers
RuleBert: Teaching Soft Rules to Pre-trained Language Models
Mohammed Saeed, Naser Ahmadi, Preslav Nakov +1
While pre-trained language models (PLMs) are the go-to solution to tackle many natural language processing problems, they are still very limited in their ability to capture and to…
Automated Fact-Checking for Assisting Human Fact-Checkers
Preslav Nakov, David Corney, Maram Hasanain +6
The reporting and the analysis of current events around the globe has expanded from professional, editor-lead journalism all the way to citizen journalism. Nowadays, politicians an…
Scrutinizer: A Mixed-Initiative Approach to Large-Scale, Data-Driven Claim Verification
Georgios Karagiannis, Mohammed Saeed, Paolo Papotti +1
Organizations such as the International Energy Agency (IEA) spend significant amounts of time and money to manually fact check text documents summarizing data. The goal of the Scru…
LIBRE: Learning Interpretable Boolean Rule Ensembles
Graziano Mita, Paolo Papotti, Maurizio Filippone +1
We present a novel method - LIBRE - to learn an interpretable classifier, which materializes as a set of Boolean rules. LIBRE uses an ensemble of bottom-up weak learners operating…
Local Embeddings for Relational Data Integration
Riccardo Cappuzzo, Paolo Papotti, Saravanan Thirumuruganathan
Deep learning based techniques have been recently used with promising results for data integration problems. Some methods directly use pre-trained embeddings that were trained on a…
Explainable Fact Checking with Probabilistic Answer Set Programming
Naser Ahmadi, Joohyung Lee, Paolo Papotti +1
One challenge in fact checking is the ability to improve the transparency of the decision. We present a fact checking method that uses reference information in knowledge graphs (KG…