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Multiple Distribution Shift -- Aerial (MDS-A): A Dataset for Test-Time Error Detection and Model Adaptation
Noel Ngu, Aditya Taparia, Gerardo I. Simari +5
Machine learning models assume that training and test samples are drawn from the same distribution. As such, significant differences between training and test distributions often l…
LLM-Assisted Red Teaming of Diffusion Models through "Failures Are Fated, But Can Be Faded"
Som Sagar, Aditya Taparia, Ransalu Senanayake
In large deep neural networks that seem to perform surprisingly well on many tasks, we also observe a few failures related to accuracy, social biases, and alignment with human valu…
Failures Are Fated, But Can Be Faded: Characterizing and Mitigating Unwanted Behaviors in Large-Scale Vision and Language Models
Som Sagar, Aditya Taparia, Ransalu Senanayake
In large deep neural networks that seem to perform surprisingly well on many tasks, we also observe a few failures related to accuracy, social biases, and alignment with human valu…