Dec 14, 2022
Tailored Data Augmentation to Mitigate Model Failures
We demonstrate how we can use Stable Diffusion to target a model's failure modes
Nov 23, 2022
ModelDiff: A Framework for Comparing Learning Algorithms
We introduce a framework for comparing ML models trained with different learning algorithms.
Nov 3, 2022
Raising the Cost of Malicious AI-Powered Image Editing
Inspired by an episode of the Daily Show, we hacked together a technique for "immunizing" images against being edited by diffusion models.
Jul 12, 2022
A Data-Based Perspective on Transfer Learning
We present a framework for pinpointing the impact of the source datasets in transfer learning.
Jul 7, 2022
When does Bias Transfer in Transfer Learning?
We demonstrate that biases from pre-trained models can persist even after fine-tuning.
Jun 30, 2022
Distilling Model Failures as Directions in Latent Space
We demonstrate how to distill patterns of model errors as directions in a latent space.
May 11, 2022
Uncovering Brittleness with Datamodels
In the second part of our datamodels series, we use datamodels to identify and study a new form of model brittleness.
Apr 20, 2022
Missingness Bias in Model Debugging
We demonstrate how current missingness approximations introduce biases into model debugging.
