5 papers
BiasTrace: Linking Reasoning Behaviours to Biased Outputs in LLMs
Varsha Ramineni, Hossein A. Rahmani, Jerome Ramos +2
LLMs exhibit social biases that can produce inaccurate and discriminatory inferences, posing risks in high-stakes applications. While prior work has made progress in measuring and…
Towards Understanding Bias in Synthetic Data for Evaluation
Hossein A. Rahmani, Varsha Ramineni, Emine Yilmaz +2
Test collections are crucial for evaluating Information Retrieval (IR) systems. Creating a diverse set of user queries for these collections can be challenging, and obtaining relev…
Beyond Internal Data: Bounding and Estimating Fairness from Incomplete Data
Varsha Ramineni, Hossein A. Rahmani, Emine Yilmaz +1
Ensuring fairness in AI systems is critical, especially in high-stakes domains such as lending, hiring, and healthcare. This urgency is reflected in emerging global regulations tha…
Beyond Internal Data: Constructing Complete Datasets for Fairness Testing
Varsha Ramineni, Hossein A. Rahmani, Emine Yilmaz +1
As AI becomes prevalent in high-risk domains and decision-making, it is essential to test for potential harms and biases. This urgency is reflected by the global emergence of AI re…
Understanding the Role of User Profile in the Personalization of Large Language Models
Bin Wu, Zhengyan Shi, Hossein A. Rahmani +2
Utilizing user profiles to personalize Large Language Models (LLMs) has been shown to enhance the performance on a wide range of tasks. However, the precise role of user profiles a…