1 citations · 1 across the 3 of their papers we have counts for
4 papers
Using Set Learning to Improve Set-Valued Classifiers on Long-tailed Data
Kevin Kasa, Scott C. Lowe, Graham W. Taylor
Set-valued classification (SVC) offers a practical approach to communicating uncertainty while maintaining accuracy by predicting variable-sized sets per input rather than fixed-si…
Indirect Prompt Injections: Are Firewalls All You Need, or Stronger Benchmarks?
Rishika Bhagwatkar, Kevin Kasa, Abhay Puri +5
AI agents are vulnerable to indirect prompt injection attacks, where malicious instructions embedded in external content or tool outputs cause unintended or harmful behavior. Inspi…
Adapting Prediction Sets to Distribution Shifts Without Labels
Kevin Kasa, Zhiyu Zhang, Heng Yang +1
Recently there has been a surge of interest to deploy confidence set predictions rather than point predictions in machine learning. Unfortunately, the effectiveness of such predict…
Empirically Validating Conformal Prediction on Modern Vision Architectures Under Distribution Shift and Long-tailed Data
Kevin Kasa, Graham W. Taylor
Conformal prediction has emerged as a rigorous means of providing deep learning models with reliable uncertainty estimates and safety guarantees. Yet, its performance is known to d…