10 citations · 10 across the 3 of their papers we have counts for
Showing cs.CRShow all
2 papers · 1 filter
cs.CR2026
Adversarial Benchmarks and BenchDoor Attacks: Exploiting Benchmark Incentives for Backdoor Attacks
Yixin Wu, Rachel Hong, Jamie Morgenstern +1
Machine learning benchmarks act as guideposts for model development and spur the creation of training datasets intended to improve benchmark scores. We introduce BenchDoor, a famil…
cs.CR2025
A Common Pool of Privacy Problems: Legal and Technical Lessons from a Large-Scale Web-Scraped Machine Learning Dataset
Rachel Hong, Jevan Hutson, William Agnew +3
We investigate the contents of web-scraped data for training AI systems, at sizes where human dataset curators and compilers no longer manually annotate every sample. Building off…