2 citations · 5 across the 9 of their papers we have counts for
6 papers · 1 filter
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…
Purdah and Patriarchy: Evaluating and Mitigating South Asian Biases in Open-Ended Multilingual LLM Generations
Mamnuya Rinki, Chahat Raj, Anjishnu Mukherjee +1
Evaluations of Large Language Models (LLMs) often overlook intersectional and culturally specific biases, particularly in underrepresented multilingual regions like South Asia. Thi…
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…
Global Voices, Local Biases: Socio-Cultural Prejudices across Languages
Anjishnu Mukherjee, Chahat Raj, Ziwei Zhu +1
Human biases are ubiquitous but not uniform: disparities exist across linguistic, cultural, and societal borders. As large amounts of recent literature suggest, language models (LM…
A Review of Web Infodemic Analysis and Detection Trends across Multi-modalities using Deep Neural Networks
Chahat Raj, Priyanka Meel
Fake news and misinformation are a matter of concern for people around the globe. Users of the internet and social media sites encounter content with false information much frequen…