2 citations · 3 across the 8 of their papers we have counts for
9 papers
FIBER: A Multilingual Evaluation Resource for Factual Inference Bias
Evren Ayberk Munis, Deniz Yılmaz, Arianna Muti +1
Large language models are widely used across domains, yet there are concerns about their factual reliability and biases. Factual knowledge probing offers a systematic means to eval…
Challenging the Abilities of Large Language Models in Italian: a Community Initiative
Malvina Nissim, Danilo Croce, Viviana Patti +78
The rapid progress of Large Language Models (LLMs) has transformed natural language processing and broadened its impact across research and society. Yet, systematic evaluation of t…
Generative AI Practices, Literacy, and Divides: An Empirical Analysis in the Italian Context
Beatrice Savoldi, Giuseppe Attanasio, Olga Gorodetskaya +10
The rise of generative AI (GenAI) chatbots accessible via conversational interfaces is transforming digital interactions and holds economic promise. However, these tools might deep…
The CLEF-2025 CheckThat! Lab: Subjectivity, Fact-Checking, Claim Normalization, and Retrieval
Firoj Alam, Julia Maria Struß, Tanmoy Chakraborty +11
The CheckThat! lab aims to advance the development of innovative technologies designed to identify and counteract online disinformation and manipulation efforts across various lang…
Untangling Hate Speech Definitions: A Semantic Componential Analysis Across Cultures and Domains
Katerina Korre, Arianna Muti, Federico Ruggeri +1
Hate speech relies heavily on cultural influences, leading to varying individual interpretations. For that reason, we propose a Semantic Componential Analysis (SCA) framework for a…
Language is Scary when Over-Analyzed: Unpacking Implied Misogynistic Reasoning with Argumentation Theory-Driven Prompts
Arianna Muti, Federico Ruggeri, Khalid Al-Khatib +2
We propose misogyny detection as an Argumentative Reasoning task and we investigate the capacity of large language models (LLMs) to understand the implicit reasoning used to convey…
Let Guidelines Guide You: A Prescriptive Guideline-Centered Data Annotation Methodology
Federico Ruggeri, Eleonora Misino, Arianna Muti +3
We introduce the Guideline-Centered Annotation Methodology (GCAM), a novel data annotation methodology designed to report the annotation guidelines associated with each data sample…
PejorativITy: Disambiguating Pejorative Epithets to Improve Misogyny Detection in Italian Tweets
Arianna Muti, Federico Ruggeri, Cagri Toraman +6
Misogyny is often expressed through figurative language. Some neutral words can assume a negative connotation when functioning as pejorative epithets. Disambiguating the meaning of…
A Corpus for Sentence-level Subjectivity Detection on English News Articles
Francesco Antici, Andrea Galassi, Federico Ruggeri +5
We develop novel annotation guidelines for sentence-level subjectivity detection, which are not limited to language-specific cues. We use our guidelines to collect NewsSD-ENG, a co…