2 citations · 4 across the 14 of their papers we have counts for
15 papers
The Ghost Annotator: a Framework to Explore Human Label Variation in Content Moderation through Conformal Prediction
Mirko Lai, Alessandra Urbinati, Simona Frenda +2
Current research primarily focuses on model performance, while comparatively less attention has been devoted to uncertainty estimation, particularly in settings where LLMs are incr…
Epistemic Injustice in Language Models: An Audit of Pretraining Filters and Guardrails
Marco Antonio Stranisci, A Pranav, Rossana Damiano +2
Modern language models rely on pretraining filters to remove undesirable content from training corpora and inference-time guardrails to suppress undesirable outputs during deployme…
SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization
Usman Naseem, Robert Geislinger, Juan Ren +31
We present SemEval-2026 Task 9, a shared task on online polarization detection, covering 22 languages and comprising over 110K annotated instances. Each data instance is multi-labe…
TailNLG: A Multilingual Benchmark Addressing Verbalization of Long-Tail Entities
Lia Draetta, Michael Oliverio, Virginia Ramón-Ferrer +6
The automatic verbalization of structured knowledge is a key task for making knowledge graphs accessible to non-expert users and supporting retrieval-augmented generation systems.…
Conspiracy Frame: a Semiotically-Driven Approach for Conspiracy Theories Detection
Heidi Campana Piva, Shaina Ashraf, Maziar Kianimoghadam Jouneghani +4
Conspiracy theories are anti-authoritarian narratives that lead to social conflict, impacting how people perceive political information. To help in understanding this issue, we int…
Are you sure? Measuring models bias in content moderation through uncertainty
Alessandra Urbinati, Mirko Lai, Simona Frenda +1
Automatic content moderation is crucial to ensuring safety in social media. Language Model-based classifiers are being increasingly adopted for this task, but it has been shown tha…
What Are They Filtering Out? An Experimental Benchmark of Filtering Strategies for Harm Reduction in Pretraining Datasets
Marco Antonio Stranisci, Christian Hardmeier
Data filtering strategies are a crucial component to develop safe Large Language Models (LLM), since they support the removal of harmful contents from pretraining datasets. There i…
That is Unacceptable: the Moral Foundations of Canceling
Soda Marem Lo, Oscar Araque, Rajesh Sharma +1
Canceling is a morally-driven phenomenon that hinders the development of safe social media platforms and contributes to ideological polarization. To address this issue we present t…
Dealing with Controversy: An Emotion and Coping Strategy Corpus Based on Role Playing
Enrica Troiano, Sofie Labat, Marco Antonio Stranisci +3
There is a mismatch between psychological and computational studies on emotions. Psychological research aims at explaining and documenting internal mechanisms of these phenomena, w…
The World Literature Knowledge Graph
Marco Antonio Stranisci, Eleonora Bernasconi, Viviana Patti +3
Digital media have enabled the access to unprecedented literary knowledge. Authors, readers, and scholars are now able to discover and share an increasing amount of information abo…
Wikibio: a Semantic Resource for the Intersectional Analysis of Biographical Events
Marco Antonio Stranisci, Rossana Damiano, Enrico Mensa +3
Biographical event detection is a relevant task for the exploration and comparison of the ways in which people's lives are told and represented. In this sense, it may support sever…
The URW-KG: a Resource for Tackling the Underrepresentation of non-Western Writers
Marco Antonio Stranisci, Giuseppe Spillo, Cataldo Musto +2
Digital media have enabled the access to unprecedented literary knowledge. Authors, readers, and scholars are now able to discover and share an increasing amount of information abo…
O-Dang! The Ontology of Dangerous Speech Messages
Marco A. Stranisci, Simona Frenda, Mirko Lai +5
Inside the NLP community there is a considerable amount of language resources created, annotated and released every day with the aim of studying specific linguistic phenomena. Desp…
Guidelines and a Corpus for Extracting Biographical Events
Marco Antonio Stranisci, Enrico Mensa, Ousmane Diakite +2
Despite biographies are widely spread within the Semantic Web, resources and approaches to automatically extract biographical events are limited. Such limitation reduces the amount…
APPReddit: a Corpus of Reddit Posts Annotated for Appraisal
Marco Antonio Stranisci, Simona Frenda, Eleonora Ceccaldi +3
Despite the large number of computational resources for emotion recognition, there is a lack of data sets relying on appraisal models. According to Appraisal theories, emotions are…