157 citations · 214 across the 24 of their papers we have counts for
24 papers
Who Trusts AI with Their Emotions? Trust Formation and Sociodemographic Variation in LLM Use for Emotional Support
Natalia Amat-Lefort, Mert Yazan, Amanda Cercas Curry +1
Trust in AI for emotional support is not universal; it is shaped by who users are, where they come from, and what they value. Yet research in this area lacks validated psychometric…
Affective AI Safety: The Missing Piece in LLM Safety
Carolin Ifländer, Alba Curry, Flor Miriam Plaza-del-Arco +1
AI safety research has focused predominantly on epistemic and physical harms (e.g., misinformation, bias, system reliability) while the risks that arise from AI systems' engagement…
P1SCO: Social Dimensions from a Perspectivist Lens
Amanda Cercas Curry, Gianmarco de Francisci Morales, Luca Maria Aiello
We introduce P1SCO, a dataset of social media comments collected from three distinct platforms, annotated according to ten social dimensions to capture the diversity of social inte…
Learning Perspectivist Social Meaning via Demographic-Conditioned Fusion Embeddings
Amanda Cercas Curry, Lucio La Cava, Luca Maria Aiello +1
Social meaning in language is inherently perspectival, varying across annotator backgrounds, demographics, and ideological positions. However, most NLP systems collapse this variat…
From Chatbots to Confidants: A Cross-Cultural Study of LLM Adoption for Emotional Support
Natalia Amat-Lefort, Mert Yazan, Amanda Cercas Curry +1
Large Language Models (LLMs) are increasingly used not only for instrumental tasks, but as always-available and non-judgmental confidants for emotional support. Yet what drives ado…
Do Large Language Models Adapt to Language Variation across Socioeconomic Status?
Elisa Bassignana, Mike Zhang, Dirk Hovy +1
Humans adjust their linguistic style to the audience they are addressing. However, the extent to which LLMs adapt to different social contexts is largely unknown. As these models i…