60 citations · 77 across the 6 of their papers we have counts for
6 papers
IMPACT: Inflectional Morphology Probes Across Complex Typologies
Mohammed J. Saeed, Tommi Vehvilainen, Evgeny Fedoseev +2
Large Language Models (LLMs) have shown significant progress on various multilingual benchmarks and are increasingly used to generate and evaluate text in non-English languages. Ho…
Querying Large Language Models with SQL
Mohammed Saeed, Nicola De Cao, Paolo Papotti
In many use-cases, information is stored in text but not available in structured data. However, extracting data from natural language text to precisely fit a schema, and thus enabl…
Crowdsourced Fact-Checking at Twitter: How Does the Crowd Compare With Experts?
Mohammed Saeed, Nicolas Traub, Maelle Nicolas +2
Fact-checking is one of the effective solutions in fighting online misinformation. However, traditional fact-checking is a process requiring scarce expert human resources, and thus…
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…
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…
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…