215 citations · 227 across the 4 of their papers we have counts for
4 papers
Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping
Jesse Dodge, Gabriel Ilharco, Roy Schwartz +3
Fine-tuning pretrained contextual word embedding models to supervised downstream tasks has become commonplace in natural language processing. This process, however, is often brittl…
Knowledge Enhanced Contextual Word Representations
Matthew E. Peters, Mark Neumann, Robert L. Logan +4
Contextual word representations, typically trained on unstructured, unlabeled text, do not contain any explicit grounding to real world entities and are often unable to remember fa…
Online Submodular Maximization with Preemption
Niv Buchbinder, Moran Feldman, Roy Schwartz
Submodular function maximization has been studied extensively in recent years under various constraints and models. The problem plays a major role in various disciplines. We study…
Comparing Apples and Oranges: Query Tradeoff in Submodular Maximization
Niv Buchbinder, Moran Feldman, Roy Schwartz
Fast algorithms for submodular maximization problems have a vast potential use in applicative settings, such as machine learning, social networks, and economics. Though fast algori…