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20232026
most citedBeyond Aesthetics: Cultural Competence in Text-to-Image Models

2 citations · 7 across the 19 of their papers we have counts for

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8 papers · 1 filter

cs.AI2025★ 1 cited

Humanlike AI Design Increases Anthropomorphism but Yields Divergent Outcomes on Engagement and Trust Globally

Robin Schimmelpfennig, Mark Díaz, Vinodkumar Prabhakaran +1

Over a billion users globally interact with AI systems engineered to mimic human traits. This development raises concerns that anthropomorphism, the attribution of human characteri…

cs.HC2025

Taxonomy of User Needs and Actions

Renee Shelby, Fernando Diaz, Vinodkumar Prabhakaran

The growing ubiquity of conversational AI highlights the need for frameworks that capture not only users' instrumental goals but also the situated, adaptive, and social practices t…

cs.HC2025

"Just a strange pic": Evaluating 'safety' in GenAI Image safety annotation tasks from diverse annotators' perspectives

Ding Wang, Mark Díaz, Charvi Rastogi +10

Understanding what constitutes safety in AI-generated content is complex. While developers often rely on predefined taxonomies, real-world safety judgments also involve personal, s…

cs.LG2025

Whose View of Safety? A Deep DIVE Dataset for Pluralistic Alignment of Text-to-Image Models

Charvi Rastogi, Tian Huey Teh, Pushkar Mishra +10

Current text-to-image (T2I) models often fail to account for diverse human experiences, leading to misaligned systems. We advocate for pluralistic alignment, where an AI understand…

cs.CY2025

Decoding Safety Feedback from Diverse Raters: A Data-driven Lens on Responsiveness to Severity

Pushkar Mishra, Charvi Rastogi, Stephen R. Pfohl +9

Ensuring the safety of Generative AI requires a nuanced understanding of pluralistic viewpoints. In this paper, we introduce a novel data-driven approach for analyzing ordinal safe…

cs.CL2025

Towards Geo-Culturally Grounded LLM Generations

Piyawat Lertvittayakumjorn, David Kinney, Vinodkumar Prabhakaran +2

Generative large language models (LLMs) have demonstrated gaps in diverse cultural awareness across the globe. We investigate the effect of retrieval augmented generation and searc…

cs.CL2025★ 1 cited

Risks of Cultural Erasure in Large Language Models

Rida Qadri, Aida M. Davani, Kevin Robinson +1

Large language models are increasingly being integrated into applications that shape the production and discovery of societal knowledge such as search, online education, and travel…

cs.CY2025

A Comprehensive Framework to Operationalize Social Stereotypes for Responsible AI Evaluations

Aida Davani, Sunipa Dev, Héctor Pérez-Urbina +1

Societal stereotypes are at the center of a myriad of responsible AI interventions targeted at reducing the generation and propagation of potentially harmful outcomes. While these…