no code implementations • 10 Jul 2023 • Zhili Feng, Anna Bair, J. Zico Kolter
This method first automatically generates multiple visual descriptions of each class via a large language model (LLM), then uses a VLM to translate these descriptions to a set of visual feature embeddings of each image, and finally uses sparse logistic regression to select a relevant subset of these features to classify each image.
no code implementations • 25 Jun 2023 • Anna Bair, Hongxu Yin, Maying Shen, Pavlo Molchanov, Jose Alvarez
Robustness and compactness are two essential attributes of deep learning models that are deployed in the real world.
3 code implementations • 20 Jun 2023 • MingJie Sun, Zhuang Liu, Anna Bair, J. Zico Kolter
Motivated by the recent observation of emergent large magnitude features in LLMs, our approach prunes weights with the smallest magnitudes multiplied by the corresponding input activations, on a per-output basis.
no code implementations • NeurIPS 2021 • Leslie Rice, Anna Bair, huan zhang, J. Zico Kolter
Several recent works in machine learning have focused on evaluating the test-time robustness of a classifier: how well the classifier performs not just on the target domain it was trained upon, but upon perturbed examples.