24 citations · 46 across the 10 of their papers we have counts for
10 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…
Responsible Evaluation of AI for Mental Health
Hiba Arnaout, Anmol Goel, H. Andrew Schwartz +13
Although artificial intelligence (AI) shows growing promise for mental health care, current approaches to evaluating AI tools in this domain remain fragmented and poorly aligned wi…
No for Some, Yes for Others: Persona Prompts and Other Sources of False Refusal in Language Models
Flor Miriam Plaza-del-Arco, Paul Röttger, Nino Scherrer +3
Large language models (LLMs) are increasingly integrated into our daily lives and personalized. However, LLM personalization might also increase unintended side effects. Recent wor…
MSTS: A Multimodal Safety Test Suite for Vision-Language Models
Paul Röttger, Giuseppe Attanasio, Felix Friedrich +19
Vision-language models (VLMs), which process image and text inputs, are increasingly integrated into chat assistants and other consumer AI applications. Without proper safeguards,…
Language Model Council: Democratically Benchmarking Foundation Models on Highly Subjective Tasks
Justin Zhao, Flor Miriam Plaza-del-Arco, Benjamin Genchel +1
As Large Language Models (LLMs) continue to evolve, evaluating them remains a persistent challenge. Many recent evaluations use LLMs as judges to score outputs from other LLMs, oft…