2 citations · 2 across the 2 of their papers we have counts for
5 papers
Debias It Yourself: Teaching LLMs Cognitive Bias Mitigation Interventions
Chahat Raj, Sina Mansouri, Aylin Caliskan +2
Bias has long been studied in social psychology and cognitive science, where decades of research have produced a body of validated interventions that reduce stereotypical thinking…
Talent or Luck? Evaluating Attribution Bias in Large Language Models
Chahat Raj, Mahika Banerjee, Jinhao Pan +3
When a student fails an exam, do we tend to blame their effort or the test's difficulty? Attribution, defined as how reasons are assigned to event outcomes, shapes perceptions, rei…
VIGNETTE: Socially Grounded Bias Evaluation for Vision-Language Models
Chahat Raj, Bowen Wei, Aylin Caliskan +2
While bias in large language models (LLMs) is well-studied, similar concerns in vision-language models (VLMs) have received comparatively less attention. Existing VLM bias studies…
Breaking Bias, Building Bridges: Evaluation and Mitigation of Social Biases in LLMs via Contact Hypothesis
Chahat Raj, Anjishnu Mukherjee, Aylin Caliskan +2
Large Language Models (LLMs) perpetuate social biases, reflecting prejudices in their training data and reinforcing societal stereotypes and inequalities. Our work explores the pot…
BiasDora: Exploring Hidden Biased Associations in Vision-Language Models
Chahat Raj, Anjishnu Mukherjee, Aylin Caliskan +2
Existing works examining Vision-Language Models (VLMs) for social biases predominantly focus on a limited set of documented bias associations, such as gender:profession or race:cri…