9 papers
Context Shapes LLMs Retrieval-Augmented Fact-Checking Effectiveness
Pietro Bernardelle, Stefano Civelli, Kevin Roitero +1
Large language models (LLMs) show strong reasoning abilities across diverse tasks, yet their performance on extended contexts remains inconsistent. While prior research has emphasi…
Ideology-Based LLMs for Content Moderation
Stefano Civelli, Pietro Bernardelle, Nardiena A. Pratama +1
Large language models (LLMs) are increasingly used in content moderation systems, where ensuring fairness and neutrality is essential. In this study, we examine how persona adoptio…
The Impact of Persona-based Political Perspectives on Hateful Content Detection
Stefano Civelli, Pietro Bernardelle, Gianluca Demartini
While pretraining language models with politically diverse content has been shown to improve downstream task fairness, such approaches require significant computational resources o…
Enhancing Media Literacy: The Effectiveness of (Human) Annotations and Bias Visualizations on Bias Detection
Timo Spinde, Fei Wu, Wolfgang Gaissmaier +2
Marking biased texts is a practical approach to increase media bias awareness among news consumers. However, little is known about the generalizability of such awareness to new top…
MiningGPT -- A Domain-Specific Large Language Model for the Mining Industry
Kurukulasooriya Fernando ana Gianluca Demartini
Recent advancements of generative LLMs (Large Language Models) have exhibited human-like language capabilities but have shown a lack of domain-specific understanding. Therefore, th…
Mapping and Influencing the Political Ideology of Large Language Models using Synthetic Personas
Pietro Bernardelle, Leon Fröhling, Stefano Civelli +3
The analysis of political biases in large language models (LLMs) has primarily examined these systems as single entities with fixed viewpoints. While various methods exist for meas…