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Aylin Caliskan

4 papers hereh-index 3127 citations9 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CY3
  • cs.CL1
same name
  • Aylin Caliskan — 6 papers, h 3
  • Aylin Caliskan — 3 papers, h 3
  • Aylin Caliskan — 3 papers, h 3
  • Aylin Caliskan — 3 papers, h 3
  • Aylin Caliskan — 1 paper, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.CY2026

Resume Screening, Fast and Slow: (Biased) AI Recommendations' Influence on Human Decision Making

Kyra Wilson, Mattea Sim, Anna-Maria Gueorguieva +2

AI is increasingly being used collaboratively with people to make decisions in high-stakes domains, but this new paradigm is still not well-understood in many respects -- particula…

cs.CY2026

VEAT Quantifies Implicit Associations in Text-to-Video Generator Sora and Reveals Challenges in Bias Mitigation

Yongxu Sun, Michael Saxon, Ian Yang +2

Text-to-Video (T2V) generators such as Sora raise concerns about whether generated content reflects societal bias. We extend embedding-association tests from words and images to vi…

cs.CL2025

Identifying Features Associated with Bias Against 93 Stigmatized Groups in Language Models and Guardrail Model Safety Mitigation

Anna-Maria Gueorguieva, Aylin Caliskan

Large language models (LLMs) have been shown to exhibit social bias, however, bias towards non-protected stigmatized identities remain understudied. Furthermore, what social featur…

cs.CY2025

No Thoughts Just AI: Biased LLM Hiring Recommendations Alter Human Decision Making and Limit Human Autonomy

Kyra Wilson, Mattea Sim, Anna-Maria Gueorguieva +1

In this study, we conduct a resume-screening experiment (N=528) where people collaborate with simulated AI models exhibiting race-based preferences (bias) to evaluate candidates fo…

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