25 citations · 30 across the 5 of their papers we have counts for
5 papers
Do LLMs Ask the Right Questions? Evaluating GPT-Generated Surveys as Instruments for Measuring Social Attitudes
Tina Behzad, Wenbo Li, Reuben Kline +1
Understanding human beliefs and social attitudes often relies on carefully designed survey instruments. Recent work has suggested that large language models (LLMs) could automate p…
ImputeViz: A Visual Analytics Dashboard for Diagnosing Missing Data and Comparing Imputation Methods
Aitik Dandapat, Lalith Punepalle Raveendrareddy, Mithilesh Kumar Singh +1
Missing data is a persistent obstacle in scientific, social science, and public health research, often biasing analyses and placing accountability on analysts for how they handle m…
FairPlay: A Collaborative Approach to Mitigate Bias in Datasets for Improved AI Fairness
Tina Behzad, Mithilesh Kumar Singh, Anthony J. Ripa +1
The issue of fairness in decision-making is a critical one, especially given the variety of stakeholder demands for differing and mutually incompatible versions of fairness. Adopti…
Explainable XR: Understanding User Behaviors of XR Environments using LLM-assisted Analytics Framework
Yoonsang Kim, Zainab Aamir, Mithilesh Singh +3
We present Explainable XR, an end-to-end framework for analyzing user behavior in diverse eXtended Reality (XR) environments by leveraging Large Language Models (LLMs) for data int…
Belief Miner: A Methodology for Discovering Causal Beliefs and Causal Illusions from General Populations
Shahreen Salim, Md Naimul Hoque, Klaus Mueller
Causal belief is a cognitive practice that humans apply everyday to reason about cause and effect relations between factors, phenomena, or events. Like optical illusions, humans ar…