160 citations · 169 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 160 cited
Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution
Ananya Kumar, Aditi Raghunathan, Robbie Jones +2
When transferring a pretrained model to a downstream task, two popular methods are full fine-tuning (updating all the model parameters) and linear probing (updating only the last l…
cs.LG2020★ 9 cited
In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness
Sang Michael Xie, Ananya Kumar, Robbie Jones +3
Consider a prediction setting with few in-distribution labeled examples and many unlabeled examples both in- and out-of-distribution (OOD). The goal is to learn a model which perfo…