1 citations · 1 across the 3 of their papers we have counts for
4 papers
Can Optimization Trajectories Explain Multi-Task Transfer?
David Mueller, Mark Dredze, Nicholas Andrews
Despite the widespread adoption of multi-task training in deep learning, little is understood about how multi-task learning (MTL) affects generalization. Prior work has conjectured…
Do Text-to-Text Multi-Task Learners Suffer from Task Conflict?
David Mueller, Nicholas Andrews, Mark Dredze
Traditional multi-task learning architectures train a single model across multiple tasks through a shared encoder followed by task-specific decoders. Learning these models often re…
Ensemble Distillation for Structured Prediction: Calibrated, Accurate, Fast-Choose Three
Steven Reich, David Mueller, Nicholas Andrews
Modern neural networks do not always produce well-calibrated predictions, even when trained with a proper scoring function such as cross-entropy. In classification settings, simple…
Sources of Transfer in Multilingual Named Entity Recognition
David Mueller, Nicholas Andrews, Mark Dredze
Named-entities are inherently multilingual, and annotations in any given language may be limited. This motivates us to consider polyglot named-entity recognition (NER), where one m…