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Zihang Dai
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2020 – today
- 2023
- [j1]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: 126658 (2023) - 2022
- [c25]Zirui Wang, Jiahui Yu, Adams Wei Yu, Zihang Dai, Yulia Tsvetkov, Yuan Cao:
SimVLM: Simple Visual Language Model Pretraining with Weak Supervision. ICLR 2022 - [c24]Weizhe Hua, Zihang Dai, Hanxiao Liu, Quoc V. Le:
Transformer Quality in Linear Time. ICML 2022: 9099-9117 - [i26]Weizhe Hua, Zihang Dai, Hanxiao Liu, Quoc V. Le:
Transformer Quality in Linear Time. CoRR abs/2202.10447 (2022) - 2021
- [c23]Hieu Pham, Zihang Dai, Qizhe Xie, Quoc V. Le:
Meta Pseudo Labels. CVPR 2021: 11557-11568 - [c22]Zihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan:
CoAtNet: Marrying Convolution and Attention for All Data Sizes. NeurIPS 2021: 3965-3977 - [c21]David R. So, Wojciech Manke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V. Le:
Searching for Efficient Transformers for Language Modeling. NeurIPS 2021: 6010-6022 - [c20]Hanxiao Liu, Zihang Dai, David R. So, Quoc V. Le:
Pay Attention to MLPs. NeurIPS 2021: 9204-9215 - [c19]Hongyu Ren, Hanjun Dai, Zihang Dai, Mengjiao Yang, Jure Leskovec, Dale Schuurmans, Bo Dai:
Combiner: Full Attention Transformer with Sparse Computation Cost. NeurIPS 2021: 22470-22482 - [i25]Hanxiao Liu, Zihang Dai, David R. So, Quoc V. Le:
Pay Attention to MLPs. CoRR abs/2105.08050 (2021) - [i24]Zihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan:
CoAtNet: Marrying Convolution and Attention for All Data Sizes. CoRR abs/2106.04803 (2021) - [i23]Hongyu Ren, Hanjun Dai, Zihang Dai, Mengjiao Yang, Jure Leskovec, Dale Schuurmans, Bo Dai:
Combiner: Full Attention Transformer with Sparse Computation Cost. CoRR abs/2107.05768 (2021) - [i22]Zirui Wang, Jiahui Yu, Adams Wei Yu, Zihang Dai, Yulia Tsvetkov, Yuan Cao:
SimVLM: Simple Visual Language Model Pretraining with Weak Supervision. CoRR abs/2108.10904 (2021) - [i21]David R. So, Wojciech Manke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V. Le:
Primer: Searching for Efficient Transformers for Language Modeling. CoRR abs/2109.08668 (2021) - [i20]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 abs/2111.10050 (2021) - 2020
- [c18]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 - [c17]Mandy Guo, Zihang Dai, Denny Vrandecic, Rami Al-Rfou:
Wiki-40B: Multilingual Language Model Dataset. LREC 2020: 2440-2452 - [c16]Zihang Dai, Guokun Lai, Yiming Yang, Quoc Le:
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing. NeurIPS 2020 - [c15]Qizhe Xie, Zihang Dai, Eduard H. Hovy, Thang Luong, Quoc Le:
Unsupervised Data Augmentation for Consistency Training. NeurIPS 2020 - [i19]Hieu Pham, Qizhe Xie, Zihang Dai, Quoc V. Le:
Meta Pseudo Labels. CoRR abs/2003.10580 (2020) - [i18]Zihang Dai, Guokun Lai, Yiming Yang, Quoc V. Le:
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing. CoRR abs/2006.03236 (2020) - [i17]Guokun Lai, Zihang Dai, Yiming Yang:
Unsupervised Parallel Corpus Mining on Web Data. CoRR abs/2009.08595 (2020)
2010 – 2019
- 2019
- [c14]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: 6626-6633 - [c13]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: 2978-2988 - [c12]Zirui Wang, Zihang Dai, Barnabás Póczos, Jaime G. Carbonell:
Characterizing and Avoiding Negative Transfer. CVPR 2019: 11293-11302 - [c11]Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, Quoc V. Le:
XLNet: Generalized Autoregressive Pretraining for Language Understanding. NeurIPS 2019: 5754-5764 - [c10]Guokun Lai, Zihang Dai, Yiming Yang, Shinjae Yoo:
Re-examination of the Role of Latent Variables in Sequence Modeling. NeurIPS 2019: 7812-7822 - [i16]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 abs/1901.02860 (2019) - [i15]Zihang Dai, Guokun Lai, Yiming Yang, Shinjae Yoo:
Re-examination of the Role of Latent Variables in Sequence Modeling. CoRR abs/1902.01388 (2019) - [i14]Qizhe Xie, Zihang Dai, Eduard H. Hovy, Minh-Thang Luong, Quoc V. Le:
Unsupervised Data Augmentation. CoRR abs/1904.12848 (2019) - [i13]Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, Quoc V. Le:
XLNet: Generalized Autoregressive Pretraining for Language Understanding. CoRR abs/1906.08237 (2019) - [i12]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 abs/1910.08350 (2019) - 2018
- [c9]Zihang Dai, Qizhe Xie, Eduard H. Hovy:
From Credit Assignment to Entropy Regularization: Two New Algorithms for Neural Sequence Prediction. ACL (1) 2018: 1672-1682 - [c8]Xinyi Wang, Hieu Pham, Zihang Dai, Graham Neubig:
SwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translation. EMNLP 2018: 856-861 - [c7]Qizhe Xie, Guokun Lai, Zihang Dai, Eduard H. Hovy:
Large-scale Cloze Test Dataset Created by Teachers. EMNLP 2018: 2344-2356 - [c6]Zhilin Yang, Zihang Dai, Ruslan Salakhutdinov, William W. Cohen:
Breaking the Softmax Bottleneck: A High-Rank RNN Language Model. ICLR 2018 - [i11]Zihang Dai, Qizhe Xie, Eduard H. Hovy:
From Credit Assignment to Entropy Regularization: Two New Algorithms for Neural Sequence Prediction. CoRR abs/1804.10974 (2018) - [i10]Xinyi Wang, Hieu Pham, Zihang Dai, Graham Neubig:
SwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translation. CoRR abs/1808.07512 (2018) - [i9]Xiang Kong, Qizhe Xie, Zihang Dai, Eduard H. Hovy:
Fast and Simple Mixture of Softmaxes with BPE and Hybrid-LightRNN for Language Generation. CoRR abs/1809.09296 (2018) - [i8]Zirui Wang, Zihang Dai, Barnabás Póczos, Jaime G. Carbonell:
Characterizing and Avoiding Negative Transfer. CoRR abs/1811.09751 (2018) - 2017
- [c5]Qizhe Xie, Xuezhe Ma
, Zihang Dai, Eduard H. Hovy
An Interpretable Knowledge Transfer Model for Knowledge Base Completion. ACL (1) 2017: 950-962 - [c4]Zihang Dai, Amjad Almahairi, Philip Bachman, Eduard H. Hovy, Aaron C. Courville:
Calibrating Energy-based Generative Adversarial Networks. ICLR (Poster) 2017 - [c3]Qizhe Xie, Zihang Dai, Yulun Du, Eduard H. Hovy, Graham Neubig:
Controllable Invariance through Adversarial Feature Learning. NIPS 2017: 585-596 - [c2]Zihang Dai, Zhilin Yang, Fan Yang, William W. Cohen, Ruslan Salakhutdinov:
Good Semi-supervised Learning That Requires a Bad GAN. NIPS 2017: 6510-6520 - [i7]Zihang Dai, Amjad Almahairi, Philip Bachman, Eduard H. Hovy, Aaron C. Courville:
Calibrating Energy-based Generative Adversarial Networks. CoRR abs/1702.01691 (2017) - [i6]Qizhe Xie, Xuezhe Ma, Zihang Dai, Eduard H. Hovy:
An Interpretable Knowledge Transfer Model for Knowledge Base Completion. CoRR abs/1704.05908 (2017) - [i5]Zihang Dai, Zhilin Yang, Fan Yang, William W. Cohen, Ruslan Salakhutdinov:
Good Semi-supervised Learning that Requires a Bad GAN. CoRR abs/1705.09783 (2017) - [i4]Qizhe Xie, Zihang Dai, Yulun Du, Eduard H. Hovy, Graham Neubig:
Controllable Invariance through Adversarial Feature Learning. CoRR abs/1705.11122 (2017) - [i3]Qizhe Xie, Guokun Lai, Zihang Dai, Eduard H. Hovy:
Large-scale Cloze Test Dataset Designed by Teachers. CoRR abs/1711.03225 (2017) - [i2]Zhilin Yang, Zihang Dai, Ruslan Salakhutdinov, William W. Cohen:
Breaking the Softmax Bottleneck: A High-Rank RNN Language Model. CoRR abs/1711.03953 (2017) - 2016
- [c1]Zihang Dai, Lei Li, Wei Xu:
CFO: Conditional Focused Neural Question Answering with Large-scale Knowledge Bases. ACL (1) 2016 - [i1]Zihang Dai, Lei Li, Wei Xu:
CFO: Conditional Focused Neural Question Answering with Large-scale Knowledge Bases. CoRR abs/1606.01994 (2016)
Coauthor Index
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last updated on 2024-09-09 01:12 CEST by the dblp team
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