Zihang Dai

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 52

Top Topics

Latent Variables

Top Venues

Publications

Hieu Pham, Zihang Dai, Golnaz Ghiasi, Kenji Kawaguchi, Hanxiao Liu, Adams Wei Yu, Jiahui Yu, Yi-Ting Chen, Minh-Thang Luong, Yonghui Wu, Mingxing Tan, Quoc V. Le
Combined scaling for zero-shot transfer learning. Neurocomputing 555 (2023)
Weizhe Hua, Zihang Dai, Hanxiao Liu, Quoc V. Le
Transformer Quality in Linear Time. CoRR (2022)
Zirui Wang, Jiahui Yu, Adams Wei Yu, Zihang Dai, Yulia Tsvetkov, Yuan Cao
SimVLM: Simple Visual Language Model Pretraining with Weak Supervision. ICLR (2022)
Weizhe Hua, Zihang Dai, Hanxiao Liu, Quoc V. Le
Transformer Quality in Linear Time. ICML (2022)
Hanxiao Liu, Zihang Dai, David R. So, Quoc V. Le
Pay Attention to MLPs. NeurIPS (2021)
Hongyu Ren, Hanjun Dai, Zihang Dai, Mengjiao Yang, Jure Leskovec, Dale Schuurmans, Bo Dai
Combiner: Full Attention Transformer with Sparse Computation Cost. CoRR (2021)
David R. So, Wojciech Manke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V. Le
Primer: Searching for Efficient Transformers for Language Modeling. CoRR (2021)
Hieu Pham, Zihang Dai, Qizhe Xie, Quoc V. Le
Meta Pseudo Labels. CVPR (2021)
Zihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan
CoAtNet: Marrying Convolution and Attention for All Data Sizes. CoRR (2021)
Hanxiao Liu, Zihang Dai, David R. So, Quoc V. Le
Pay Attention to MLPs. CoRR (2021)
Zihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan
CoAtNet: Marrying Convolution and Attention for All Data Sizes. NeurIPS (2021)
Hieu Pham, Zihang Dai, Golnaz Ghiasi, Hanxiao Liu, Adams Wei Yu, Minh-Thang Luong, Mingxing Tan, Quoc V. Le
Combined Scaling for Zero-shot Transfer Learning. CoRR (2021)
Zirui Wang, Jiahui Yu, Adams Wei Yu, Zihang Dai, Yulia Tsvetkov, Yuan Cao
SimVLM: Simple Visual Language Model Pretraining with Weak Supervision. CoRR (2021)
Hongyu Ren, Hanjun Dai, Zihang Dai, Mengjiao Yang, Jure Leskovec, Dale Schuurmans, Bo Dai
Combiner: Full Attention Transformer with Sparse Computation Cost. NeurIPS (2021)
David R. So, Wojciech Manke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V. Le
Searching for Efficient Transformers for Language Modeling. NeurIPS (2021)
Zihang Dai, Guokun Lai, Yiming Yang, Quoc Le
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing. NeurIPS (2020)
Qizhe Xie, Zihang Dai, Eduard H. Hovy, Thang Luong, Quoc Le
Unsupervised Data Augmentation for Consistency Training. NeurIPS (2020)
Guokun Lai, Zihang Dai, Yiming Yang
Unsupervised Parallel Corpus Mining on Web Data. CoRR (2020)
Mandy Guo, Zihang Dai, Denny Vrandecic, Rami Al-Rfou
Wiki-40B: Multilingual Language Model Dataset. LREC (2020)
Hieu Pham, Qizhe Xie, Zihang Dai, Quoc V. Le
Meta Pseudo Labels. CoRR (2020)
Zihang Dai, Guokun Lai, Yiming Yang, Quoc V. Le
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing. CoRR (2020)
Lingpeng Kong, Cyprien de Masson d'Autume, Lei Yu, Wang Ling, Zihang Dai, Dani Yogatama
A Mutual Information Maximization Perspective of Language Representation Learning. ICLR (2020)
Guokun Lai, Zihang Dai, Yiming Yang, Shinjae Yoo
Re-examination of the Role of Latent Variables in Sequence Modeling. NeurIPS (2019)
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime G. Carbonell, Quoc Viet Le, Ruslan Salakhutdinov
Transformer-XL: Attentive Language Models beyond a Fixed-Length Context. ACL (1) (2019)
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, Quoc V. Le
XLNet: Generalized Autoregressive Pretraining for Language Understanding. CoRR (2019)
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, Quoc V. Le
XLNet: Generalized Autoregressive Pretraining for Language Understanding. NeurIPS (2019)
Zihang Dai, Guokun Lai, Yiming Yang, Shinjae Yoo
Re-examination of the Role of Latent Variables in Sequence Modeling. CoRR (2019)
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime G. Carbonell, Quoc V. Le, Ruslan Salakhutdinov
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context. CoRR (2019)
Zirui Wang, Zihang Dai, Barnabás Póczos, Jaime G. Carbonell
Characterizing and Avoiding Negative Transfer. CVPR (2019)
Qizhe Xie, Zihang Dai, Eduard H. Hovy, Minh-Thang Luong, Quoc V. Le
Unsupervised Data Augmentation. CoRR (2019)
Lingpeng Kong, Cyprien de Masson d'Autume, Wang Ling, Lei Yu, Zihang Dai, Dani Yogatama
A Mutual Information Maximization Perspective of Language Representation Learning. CoRR (2019)
Xiang Kong, Qizhe Xie, Zihang Dai, Eduard H. Hovy
Fast and Simple Mixture of Softmaxes with BPE and Hybrid-LightRNN for Language Generation. AAAI (2019)
Xinyi Wang, Hieu Pham, Zihang Dai, Graham Neubig
SwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translation. EMNLP (2018)
Zihang Dai, Qizhe Xie, Eduard H. Hovy
From Credit Assignment to Entropy Regularization: Two New Algorithms for Neural Sequence Prediction. CoRR (2018)
Xinyi Wang, Hieu Pham, Zihang Dai, Graham Neubig
SwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translation. CoRR (2018)
Zihang Dai, Qizhe Xie, Eduard H. Hovy
From Credit Assignment to Entropy Regularization: Two New Algorithms for Neural Sequence Prediction. ACL (1) (2018)
Xiang Kong, Qizhe Xie, Zihang Dai, Eduard H. Hovy
Fast and Simple Mixture of Softmaxes with BPE and Hybrid-LightRNN for Language Generation. CoRR (2018)
Qizhe Xie, Guokun Lai, Zihang Dai, Eduard H. Hovy
Large-scale Cloze Test Dataset Created by Teachers. EMNLP (2018)
Zhilin Yang, Zihang Dai, Ruslan Salakhutdinov, William W. Cohen
Breaking the Softmax Bottleneck: A High-Rank RNN Language Model. ICLR (2018)
Zirui Wang, Zihang Dai, Barnabás Póczos, Jaime G. Carbonell
Characterizing and Avoiding Negative Transfer. CoRR (2018)
Zhilin Yang, Zihang Dai, Ruslan Salakhutdinov, William W. Cohen
Breaking the Softmax Bottleneck: A High-Rank RNN Language Model. CoRR (2017)
Zihang Dai, Amjad Almahairi, Philip Bachman, Eduard H. Hovy, Aaron C. Courville
Calibrating Energy-based Generative Adversarial Networks. CoRR (2017)
Qizhe Xie, Xuezhe Ma, Zihang Dai, Eduard H. Hovy
An Interpretable Knowledge Transfer Model for Knowledge Base Completion. CoRR (2017)
Qizhe Xie, Zihang Dai, Yulun Du, Eduard H. Hovy, Graham Neubig
Controllable Invariance through Adversarial Feature Learning. NIPS (2017)
Qizhe Xie, Xuezhe Ma, Zihang Dai, Eduard H. Hovy
An Interpretable Knowledge Transfer Model for Knowledge Base Completion. ACL (1) (2017)
Qizhe Xie, Zihang Dai, Yulun Du, Eduard H. Hovy, Graham Neubig
Controllable Invariance through Adversarial Feature Learning. CoRR (2017)
Zihang Dai, Zhilin Yang, Fan Yang, William W. Cohen, Ruslan Salakhutdinov
Good Semi-supervised Learning that Requires a Bad GAN. CoRR (2017)
Zihang Dai, Zhilin Yang, Fan Yang, William W. Cohen, Ruslan Salakhutdinov
Good Semi-supervised Learning That Requires a Bad GAN. NIPS (2017)
Qizhe Xie, Guokun Lai, Zihang Dai, Eduard H. Hovy
Large-scale Cloze Test Dataset Designed by Teachers. CoRR (2017)
Zihang Dai, Amjad Almahairi, Philip Bachman, Eduard H. Hovy, Aaron C. Courville
Calibrating Energy-based Generative Adversarial Networks. ICLR (Poster) (2017)
Zihang Dai, Lei Li, Wei Xu
CFO: Conditional Focused Neural Question Answering with Large-scale Knowledge Bases. ACL (1) (2016)
Zihang Dai, Lei Li, Wei Xu
CFO: Conditional Focused Neural Question Answering with Large-scale Knowledge Bases. CoRR (2016)