1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2024
SpacTor-T5: Pre-training T5 Models with Span Corruption and Replaced Token Detection
Ke Ye, Heinrich Jiang, Afshin Rostamizadeh +6
Pre-training large language models is known to be extremely resource intensive and often times inefficient, under-utilizing the information encapsulated in the training text sequen…
cs.CV2023★ 1 cited
Two-Step Active Learning for Instance Segmentation with Uncertainty and Diversity Sampling
Ke Yu, Stephen Albro, Giulia DeSalvo +5
Training high-quality instance segmentation models requires an abundance of labeled images with instance masks and classifications, which is often expensive to procure. Active lear…
cs.LG2023
Leveraging Importance Weights in Subset Selection
Gui Citovsky, Giulia DeSalvo, Sanjiv Kumar +3
We present a subset selection algorithm designed to work with arbitrary model families in a practical batch setting. In such a setting, an algorithm can sample examples one at a ti…