10 citations · 17 across the 5 of their papers we have counts for
5 papers
Same Words, Different Judgments: How Preferences Vary Across Modalities
Aaron Broukhim, Nadir Weibel, Eshin Jolly
Preference-based reinforcement learning (PbRL) is the dominant framework for aligning AI systems to human preferences. However, evaluation protocols for such data were designed for…
Preference-Based Learning in Audio Applications: A Systematic Analysis
Aaron Broukhim, Yiran Shen, Prithviraj Ammanabrolu +1
Despite the parallel challenges that audio and text domains face in evaluating generative model outputs, preference learning remains remarkably underexplored in audio applications.…
What Did My Car Say? Impact of Autonomous Vehicle Explanation Errors and Driving Context On Comfort, Reliance, Satisfaction, and Driving Confidence
Robert Kaufman, Aaron Broukhim, David Kirsh +1
Explanations for autonomous vehicle (AV) decisions may build trust, however, explanations can contain errors. In a simulated driving study (n = 232), we tested how AV explanation e…
WARNING This Contains Misinformation: The Effect of Cognitive Factors, Beliefs, and Personality on Misinformation Warning Tag Attitudes
Robert Kaufman, Aaron Broukhim, Michael Haupt
Social media platforms enhance the propagation of online misinformation by providing large user bases with a quick means to share content. One way to disrupt the rapid disseminatio…
Using Deep Learning with Large Aggregated Datasets for COVID-19 Classification from Cough
Esin Darici Haritaoglu, Nicholas Rasmussen, Daniel C. H. Tan +12
The Covid-19 pandemic has been one of the most devastating events in recent history, claiming the lives of more than 5 million people worldwide. Even with the worldwide distributio…