1 citations · 1 across the 6 of their papers we have counts for
6 papers
Unknown Aware AI-Generated Content Attribution
Ellie Thieu, Jifan Zhang, Haoyue Bai
The rapid advancement of photorealistic generative models has made it increasingly important to attribute the origin of synthetic content, moving beyond binary real or fake detecti…
Deep Active Learning in the Open World
Tian Xie, Jifan Zhang, Haoyue Bai +1
Machine learning models deployed in open-world scenarios often encounter unfamiliar conditions and perform poorly in unanticipated situations. As AI systems advance and find applic…
AHA: Human-Assisted Out-of-Distribution Generalization and Detection
Haoyue Bai, Jifan Zhang, Robert Nowak
Modern machine learning models deployed often encounter distribution shifts in real-world applications, manifesting as covariate or semantic out-of-distribution (OOD) shifts. These…
Out-of-Distribution Learning with Human Feedback
Haoyue Bai, Xuefeng Du, Katie Rainey +2
Out-of-distribution (OOD) learning often relies heavily on statistical approaches or predefined assumptions about OOD data distributions, hindering their efficacy in addressing mul…
HYPO: Hyperspherical Out-of-Distribution Generalization
Haoyue Bai, Yifei Ming, Julian Katz-Samuels +1
Out-of-distribution (OOD) generalization is critical for machine learning models deployed in the real world. However, achieving this can be fundamentally challenging, as it require…
Image change detection with only a few samples
Ke Liu, Zhaoyi Song, Haoyue Bai
This paper considers image change detection with only a small number of samples, which is a significant problem in terms of a few annotations available. A major impediment of image…