CFO: Conditional Focused Neural Question Answering with Large-scale Knowledge Bases. - Zihang Dai; Lei Li 005; Wei Xu 017 (ACL (1), 2016)

An Interpretable Knowledge Transfer Model for Knowledge Base Completion. - Qizhe Xie; Xuezhe Ma; Zihang Dai; Eduard H. Hovy (ACL (1), 2017)

Calibrating Energy-based Generative Adversarial Networks. - Zihang Dai; Amjad Almahairi; Philip Bachman; Eduard H. Hovy; Aaron C. Courville (ICLR (Poster), 2017)

Good Semi-supervised Learning That Requires a Bad GAN. - Zihang Dai; Zhilin Yang 001; Fan Yang 058; William W. Cohen; Ruslan Salakhutdinov (NIPS, 2017)

Controllable Invariance through Adversarial Feature Learning. - Qizhe Xie; Zihang Dai; Yulun Du; Eduard H. Hovy; Graham Neubig (NIPS, 2017)

Large-scale Cloze Test Dataset Designed by Teachers. - Qizhe Xie; Guokun Lai; Zihang Dai; Eduard H. Hovy (CoRR, 2017)

From Credit Assignment to Entropy Regularization: Two New Algorithms for Neural Sequence Prediction. - Zihang Dai; Qizhe Xie; Eduard H. Hovy (ACL (1), 2018)

SwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translation. - Xinyi Wang 001; Hieu Pham; Zihang Dai; Graham Neubig (EMNLP, 2018)

Large-scale Cloze Test Dataset Created by Teachers. - Qizhe Xie; Guokun Lai; Zihang Dai; Eduard H. Hovy (EMNLP, 2018)

Breaking the Softmax Bottleneck: A High-Rank RNN Language Model. - Zhilin Yang 001; Zihang Dai; Ruslan Salakhutdinov; William W. Cohen (ICLR, 2018)

Fast and Simple Mixture of Softmaxes with BPE and Hybrid-LightRNN for Language Generation. - Xiang Kong; Qizhe Xie; Zihang Dai; Eduard H. Hovy (AAAI, 2019)

Transformer-XL: Attentive Language Models beyond a Fixed-Length Context. - Zihang Dai; Zhilin Yang 001; Yiming Yang; Jaime G. Carbonell; Quoc Viet Le; Ruslan Salakhutdinov (ACL (1), 2019)

Characterizing and Avoiding Negative Transfer. - Zirui Wang; Zihang Dai; Barnabás Póczos; Jaime G. Carbonell (CVPR, 2019)

Re-examination of the Role of Latent Variables in Sequence Modeling. - Guokun Lai; Zihang Dai; Yiming Yang; Shinjae Yoo (NeurIPS, 2019)

XLNet: Generalized Autoregressive Pretraining for Language Understanding. - Zhilin Yang 001; Zihang Dai; Yiming Yang; Jaime G. Carbonell; Ruslan Salakhutdinov; Quoc V. Le (NeurIPS, 2019)

Unsupervised Data Augmentation. - Qizhe Xie; Zihang Dai; Eduard H. Hovy; Minh-Thang Luong; Quoc V. Le (CoRR, 2019)

A Mutual Information Maximization Perspective of Language Representation Learning. - Lingpeng Kong; Cyprien de Masson d'Autume; Lei Yu 008; Wang Ling; Zihang Dai; Dani Yogatama (ICLR, 2020)

Wiki-40B: Multilingual Language Model Dataset. - Mandy Guo; Zihang Dai; Denny Vrandecic; Rami Al-Rfou (LREC, 2020)

Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing. - Zihang Dai; Guokun Lai; Yiming Yang; Quoc Le 001 (NeurIPS, 2020)

Unsupervised Data Augmentation for Consistency Training. - Qizhe Xie; Zihang Dai; Eduard H. Hovy; Thang Luong; Quoc Le 001 (NeurIPS, 2020)

Unsupervised Parallel Corpus Mining on Web Data. - Guokun Lai; Zihang Dai; Yiming Yang (CoRR, 2020)

Meta Pseudo Labels. - Hieu Pham 001; Zihang Dai; Qizhe Xie; Quoc V. Le (CVPR, 2021)

CoAtNet: Marrying Convolution and Attention for All Data Sizes. - Zihang Dai; Hanxiao Liu; Quoc V. Le; Mingxing Tan (NeurIPS, 2021)

Pay Attention to MLPs. - Hanxiao Liu; Zihang Dai; David R. So; Quoc V. Le (NeurIPS, 2021)

Combiner: Full Attention Transformer with Sparse Computation Cost. - Hongyu Ren; Hanjun Dai; Zihang Dai; Mengjiao Yang 001; Jure Leskovec; Dale Schuurmans; Bo Dai 001 (NeurIPS, 2021)

Searching for Efficient Transformers for Language Modeling. - David R. So; Wojciech Manke; Hanxiao Liu; Zihang Dai; Noam Shazeer; Quoc V. Le (NeurIPS, 2021)

Primer: Searching for Efficient Transformers for Language Modeling. - David R. So; Wojciech Manke; Hanxiao Liu; Zihang Dai; Noam Shazeer; Quoc V. Le (CoRR, 2021)

Combined Scaling for Zero-shot Transfer Learning. - Hieu Pham 001; Zihang Dai; Golnaz Ghiasi; Hanxiao Liu; Adams Wei Yu; Minh-Thang Luong; Mingxing Tan; Quoc V. Le (CoRR, 2021)

SimVLM: Simple Visual Language Model Pretraining with Weak Supervision. - Zirui Wang; Jiahui Yu; Adams Wei Yu; Zihang Dai; Yulia Tsvetkov; Yuan Cao 007 (ICLR, 2022)

Transformer Quality in Linear Time. - Weizhe Hua; Zihang Dai; Hanxiao Liu; Quoc V. Le (ICML, 2022)

Combined scaling for zero-shot transfer learning. - Hieu Pham 001; 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 (Neurocomputing, 2023)