49 citations · 80 across the 5 of their papers we have counts for
10 papers
Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning
Nan Ding, Xi Chen, Tomer Levinboim +2
Despite recent advances in its theoretical understanding, there still remains a significant gap in the ability of existing PAC-Bayesian theories on meta-learning to explain perform…
Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts
Soravit Changpinyo, Piyush Sharma, Nan Ding +1
The availability of large-scale image captioning and visual question answering datasets has contributed significantly to recent successes in vision-and-language pre-training. Howev…
Do Transformer Modifications Transfer Across Implementations and Applications?
Sharan Narang, Hyung Won Chung, Yi Tay +13
The research community has proposed copious modifications to the Transformer architecture since it was introduced over three years ago, relatively few of which have seen widespread…
Improving Text Generation Evaluation with Batch Centering and Tempered Word Mover Distance
Xi Chen, Nan Ding, Tomer Levinboim +1
Recent advances in automatic evaluation metrics for text have shown that deep contextualized word representations, such as those generated by BERT encoders, are helpful for designi…
TeaForN: Teacher-Forcing with N-grams
Sebastian Goodman, Nan Ding, Radu Soricut
Sequence generation models trained with teacher-forcing suffer from issues related to exposure bias and lack of differentiability across timesteps. Our proposed method, Teacher-For…
Attention that does not Explain Away
Nan Ding, Xinjie Fan, Zhenzhong Lan +2
Models based on the Transformer architecture have achieved better accuracy than the ones based on competing architectures for a large set of tasks. A unique feature of the Transfor…