1.8k citations · 5.3k across the 25 of their papers we have counts for
4 papers · 1 filter
Characterizing and Avoiding Negative Transfer
Zirui Wang, Zihang Dai, Barnabás Póczos +1
When labeled data is scarce for a specific target task, transfer learning often offers an effective solution by utilizing data from a related source task. However, when transferrin…
Fast and Simple Mixture of Softmaxes with BPE and Hybrid-LightRNN for Language Generation
Xiang Kong, Qizhe Xie, Zihang Dai +1
Mixture of Softmaxes (MoS) has been shown to be effective at addressing the expressiveness limitation of Softmax-based models. Despite the known advantage, MoS is practically seale…
SwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translation
Xinyi Wang, Hieu Pham, Zihang Dai +1
In this work, we examine methods for data augmentation for text-based tasks such as neural machine translation (NMT). We formulate the design of a data augmentation policy with des…
From Credit Assignment to Entropy Regularization: Two New Algorithms for Neural Sequence Prediction
Zihang Dai, Qizhe Xie, Eduard Hovy
In this work, we study the credit assignment problem in reward augmented maximum likelihood (RAML) learning, and establish a theoretical equivalence between the token-level counter…