35 citations · 145 across the 18 of their papers we have counts for
3 papers · 1 filter
Deep Transformers with Latent Depth
Xian Li, Asa Cooper Stickland, Yuqing Tang +1
The Transformer model has achieved state-of-the-art performance in many sequence modeling tasks. However, how to leverage model capacity with large or variable depths is still an o…
Diverse Ensembles Improve Calibration
Asa Cooper Stickland, Iain Murray
Modern deep neural networks can produce badly calibrated predictions, especially when train and test distributions are mismatched. Training an ensemble of models and averaging thei…
Recipes for Adapting Pre-trained Monolingual and Multilingual Models to Machine Translation
Asa Cooper Stickland, Xian Li, Marjan Ghazvininejad
There has been recent success in pre-training on monolingual data and fine-tuning on Machine Translation (MT), but it remains unclear how to best leverage a pre-trained model for a…