Zihang dai

Jul 14, 2024
Authors. Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R. Salakhutdinov, Quoc V. Le. Abstract. With the capability of modeling bidirectional contexts, denoising autoencoding based pretraining like BERT achieves better performance than pretraining approaches based on autoregressive language modeling..

9 code implementations • CVPR 2021 • Hieu Pham , Zihang Dai , Qizhe Xie , Minh-Thang Luong , Quoc V. Le. We present Meta Pseudo Labels, a semi-supervised learning method that achieves a new state-of-the-art top-1 accuracy of 90. 2% on ImageNet, which is 1. 6% better than the existing state-of-the-art.Zirui Wang, Jiahui Yu, Adams Wei Yu, Zihang Dai, Yulia Tsvetkov, Yuan Cao. ICLR 2022. Towards Zero-Label Language Learning. Zirui Wang, Adams Wei Yu, Orhan Firat, Yuan Cao. Preprint. Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models.Transformer Quality in Linear Time. We revisit the design choices in Transformers, and propose methods to address their weaknesses in handling long sequences. First, we propose a simple layer named gated attention unit, which allows the use of a weaker single-head attention with minimal quality loss. We then propose a linear approximation ...We present Meta Pseudo Labels, a semi-supervised learning method that achieves a new state-of-the-art top-1 accuracy of 90.2% on ImageNet, which is 1.6% better than the existing state-of-the-art. Like Pseudo Labels, Meta Pseudo Labels has a teacher networ.[39] Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc V Le, and Ruslan Salakhutdinov. Transformer-xl: Attentive language models beyond a fixed-length context. arXiv preprint arXiv:1901.02860 , 2019.I'm a research scientist at Google Brain. I got my Ph.D. from the School of Computer Science at CMU.Qizhe Xie 1, 2, Zihang Dai , Eduard Hovy , Minh-Thang Luong , Quoc V. Le1 1 Google Research, Brain Team, 2 Carnegie Mellon University {qizhex, dzihang, hovy}@cs.cmu.edu, {thangluong, qvl}@google.com Abstract Semi-supervised learning lately has shown much promise in improving deep learn-ing models when labeled data is scarce.Author links open overlay panel Zihang Shen 1, Jie Ma 1, Yijie Cai 1, Siyang Li 1, Dongrui Ruan 1, Shufen Dai 2, Zhi Sheng 1, Jiabao Bai 1, Daochen Yin 1, Jianfeng Ping 2, Yibin Ying 2, Canhui Yang 3, Shaoxing Qu 1, Zheng Jia 1 4Are you looking for a quick and easy getaway? Whether you’re looking to relax, explore nature, or just get away from the hustle and bustle of everyday life, there are plenty of gre...Zihang Dai 12, Guokun Lai 1, Yiming Yang , Quoc V. Le2 1Carnegie Mellon University, 2Google AI Brain Team {dzihang,guokun,yiming}@cs.cmu.edu, [email protected] Abstract With the success of language pretraining, it is highly desirable to develop more efficient architectures of good scalability that can exploit the abundant unlabeled data at a ...My mom speaks in 10,000-steps-a-day terms: “I already took my 10,000 today,” or “It’s been a 14,000-steps day.” Ever since I gave her a Fitbit in 2015 she’s been a total convert. R...If your menstruation is usually on schedule and you are late by even one day, you might be pregnant, notes BabyCenter. However, it is rather common for women to be late in their pe...Corpus ID: 195069387; XLNet: Generalized Autoregressive Pretraining for Language Understanding @inproceedings{Yang2019XLNetGA, title={XLNet: Generalized Autoregressive Pretraining for Language Understanding}, author={Zhilin Yang and Zihang Dai and Yiming Yang and Jaime G. Carbonell and Ruslan Salakhutdinov and Quoc V. Le}, booktitle={Neural Information Processing Systems}, year={2019}, url ...Conference Paper. Jun 2016. Zihang Dai. Lei Li. Wei Xu. How can we enable computers to automatically answer questions like "Who created the character Harry Potter"? Carefully built knowledge bases ...Zihang Dai, a former Google researcher and co-author of Transformer-XL, is among the veterans from tech giants and academia who will work on xAI, a startup led by Musk to understand the universe. xAI aims to challenge OpenAI's ChatGPT and has ties with Twitter and Tesla.Jul 12, 2021 · Most existing approaches leverage sparsity or low-rank assumptions in the attention matrix to reduce cost, but sacrifice expressiveness. Instead, we propose Combiner, which provides full attention capability in each attention head while maintaining low computation and memory complexity. The key idea is to treat the self-attention mechanism as a ...We present a combined scaling method - named BASIC - that achieves 85.7% top-1 accuracy on the ImageNet ILSVRC-2012 validation set without learning from any labeled ImageNet example. This accuracy surpasses best published similar models - CLIP and ALIGN - by 9.3%. Our BASIC model also shows significant improvements in robustness benchmarks. For instance, on 5 test sets with natural ...Apr 29, 2019 · Unsupervised Data Augmentation for Consistency Training. Qizhe Xie, Zihang Dai, Eduard Hovy, Minh-Thang Luong, Quoc V. Le. Semi-supervised learning lately has shown much promise in improving deep learning models when labeled data is scarce. Common among recent approaches is the use of consistency training on a large amount of unlabeled data to ...We present Meta Pseudo Labels, a semi-supervised learning method that achieves a new state-of-the-art top-1 accuracy of 90.2% on ImageNet, which is 1.6% better than the existing state-of-the-art. Like Pseudo Labels, Meta Pseudo Labels has a teacher networ.Use these national days in May to promote your business and get inspired to market your business around these unique days. May is full of holidays and celebrations that may benefit...Most moths are nocturnal and prefer to fly around at night. These moths rest in an out-of-the way place during the day. There are some moths that are active during the day; they ar...Feb 21, 2022 · Transformer Quality in Linear Time. We revisit the design choices in Transformers, and propose methods to address their weaknesses in handling long sequences. First, we propose a simple layer named gated attention unit, which allows the use of a weaker single-head attention with minimal quality loss. We then propose a linear approximation ...When it comes to significant events in history, few can match the impact and importance of D-Day. Marking the beginning of the end of World War II, D-Day was a pivotal moment that ...Planning a wedding can be overwhelming, especially if you’re looking for small simple wedding ideas that reflect your personal style and budget. Luckily, there are plenty of do-it-...With the capability of modeling bidirectional contexts, denoising autoencoding based pretraining like BERT achieves better performance than pretraining approaches based on autoregressive language modeling. However, relying on corrupting the input with masks, BERT neglects dependency between the masked positions and suffers from a pretrain-finetune discrepancy. In light of these pros and cons ...Zihang Dai's 33 research works with 4,439 citations and 10,268 reads, including: Transformer Quality in Linear Time%0 Conference Proceedings %T Wiki-40B: Multilingual Language Model Dataset %A Guo, Mandy %A Dai, Zihang %A Vrandečić, Denny %A Al-Rfou, Rami %Y Calzolari, Nicoletta %Y Béchet, Frédéric %Y Blache, Philippe %Y Choukri, Khalid %Y Cieri, Christopher %Y Declerck, Thierry %Y Goggi, Sara %Y Isahara, Hitoshi %Y Maegaard, Bente %Y Mariani, Joseph %Y Mazo, Hélène %Y Moreno, Asuncion %Y Odijk ...David R. So, Wojciech Manke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V. Le´ Google Research, Brain Team {davidso, wojciechm, hanxiaol, zihangd, noam, qvl}@google.com Abstract Large Transformer models have been central to recent advances in natural language processing. The training and inference costs of these models, however, have grownZihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan Google Research, Brain Team {zihangd,hanxiaol,qvl,tanmingxing}@google.com Abstract Transformers have attracted increasing interests in computer vision, but they still fall behind state-of-the-art convolutional networks. In this work, we show thatSwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translation. 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 desirable properties as an optimization problem, and derive a generic analytic solution.CoAtNet: Marrying Convolution and Attention for All Data Sizes. Zihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan. Transformers have attracted increasing interests in computer vision, but they still fall behind state-of-the-art convolutional networks.Introduction. XLNet is a new unsupervised language representation learning method based on a novel generalized permutation language modeling objective. Additionally, XLNet employs Transformer-XL as the backbone model, exhibiting excellent performance for language tasks involving long context.Authors. Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R. Salakhutdinov, Quoc V. Le. Abstract. With the capability of modeling bidirectional contexts, denoising autoencoding based pretraining like BERT achieves better performance than pretraining approaches based on autoregressive language modeling.According to NASA, one moon day is equal to 27 Earth days, which is the time the moon takes to complete its spin. The moon is tidally locked, so it always shows the same face to th...Father’s Day is an annual celebration that honors fathers and father figures, recognizing their contributions to the lives of their children and families. It is a day to express lo...Use these national days in May to promote your business and get inspired to market your business around these unique days. May is full of holidays and celebrations that may benefit...Controllable Invariance through Adversarial Feature Learning. Qizhe Xie, Zihang Dai, Yulun Du, Eduard Hovy, Graham Neubig. Learning meaningful representations that maintain the content necessary for a particular task while filtering away detrimental variations is a problem of great interest in machine learning.Zihang Dai 12, Guokun Lai 1, Yiming Yang , Quoc V. Le2 1Carnegie Mellon University, 2Google AI Brain Team {dzihang,guokun,yiming}@cs.cmu.edu, [email protected] Abstract With the success of language pretraining, it is highly desirable to develop more efficient architectures of good scalability that can exploit the abundant unlabeled data at a ...Transformers have a potential of learning longer-term dependency, but are limited by a fixed-length context in the setting of language modeling. We propose a novel neural architecture Transformer-XL that enables learning dependency beyond a fixed length without disrupting temporal coherence.14 code implementations • NeurIPS 2021 • Zihang Dai , Hanxiao Liu , Quoc V. Le , Mingxing Tan. Transformers have attracted increasing interests in computer vision, but they still fall behind state-of-the-art convolutional networks. Ranked #1 on Image Classification on GasHisSDB. Image ClassificationInductive Bias.Zihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan. December 2021NIPS '21: Proceedings of the 35th International Conference on Neural Information Processing Systems.2023-07-13 11:48. 据了解马斯克新公司“xAI”,12名创始成员中有4名华人,其中Guodong Zhang、Zihang Dai本科分别毕业于浙江大学以及清华大学。. 返回搜狐,查看更多. 平台声明:该文观点仅代表作者本人,搜狐号系信息发布平台,搜狐仅提供信息存储空间服务。. 据 ...Zihang Dai, Hanxiao Liu, Quoc V Le, Mingxing Tan. Abstract. Transformers have attracted increasing interests in computer vision, but they still fall behind state-of-the-art convolutional networks.We would like to show you a description here but the site won’t allow us.We propose a novel neural architecture Transformer-XL that enables learning dependency beyond a fixed length without disrupting temporal coherence. It consists of a segment-level recurrence mechanism and a …2023-07-13 11:48. 据了解马斯克新公司“xAI”,12名创始成员中有4名华人,其中Guodong Zhang、Zihang Dai本科分别毕业于浙江大学以及清华大学。. 返回搜狐,查看更多. 平台声明:该文观点仅代表作者本人,搜狐号系信息发布平台,搜狐仅提供信息存储空间服务。. 据 ...Zirui Wang1; 2, Jiahui Yu , Adams Wei Yu , Zihang Dai2, Yulia Tsvetkov3, Yuan Cao2 1Carnegie Mellon University [email protected] 2Google Research, Brain Team fjiahuiyu,adamsyuwei,zihangd,[email protected] 3University of Washington [email protected] ABSTRACT With recent progress in joint modeling of visual and textual representations,Jun 9, 2021 · CoAtNet: Marrying Convolution and Attention for All Data Sizes. Zihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan. (Submitted on 9 Jun 2021 ( v1 ), last revised 15 Sep 2021 (this version, v2)) Transformers have attracted increasing interests in computer vision, but they still fall behind state-of-the-art convolutional networks. In this work, we ...Hieu Pham, Zihang Dai, Golnaz Ghiasi, Hanxiao Liu, Adams Wei Yu Minh-Thang Luong, Mingxing Tan, Quoc V. Le Google Research, Brain Team {hyhieu,zihangd}@google.com Abstract We present a combined scaling method called BASIC that achieves 85.7% top-1 zero-shot accuracy on the ImageNet ILSVRC-2012 validation set, surpassing the best-publishedCFO: Conditional Focused Neural Question Answering with Large-scale Knowledge Bases. How can we enable computers to automatically answer questions like "Who ... 0 Zihang …Zihang Dai. [email protected]. GitHub | Google Scholar. About me I'm a research scientist at Google Brain. I got my Ph.D. from the School of Computer Science at CMU.Zirui Wang1; 2, Jiahui Yu , Adams Wei Yu , Zihang Dai2, Yulia Tsvetkov3, Yuan Cao2 1Carnegie Mellon University [email protected] 2Google Research, Brain Team fjiahuiyu,adamsyuwei,zihangd,[email protected] 3University of Washington [email protected] ABSTRACT With recent progress in joint modeling of visual and textual representations,Finding the right childminder for your little one is an important decision. Once you have made your choice, it’s time to prepare your child for their first day with their new child...Jan 9, 2019 · Zihang Dai* 1, Zhilin Y ang* 2, Yiming Y ang 1, William W. Cohen 3, Jaime Carbonell 1, Quoc V. Le 2, Ruslan Salakhutdinov 1. 1 Carnegie Mellon University, 2 Google Brain, 3 Google AIUnlike prior work, SimVLM reduces the training complexity by exploiting large-scale weak supervision, and is trained end-to-end with a single prefix language modeling objective. Without utilizing extra data or task-specific customization, the resulting model significantly outperforms previous pretraining methods and achieves new state-of-the ...Re-examination of the Role of Latent Variables in Sequence Modeling. 1 code implementation • NeurIPS 2019 • Zihang Dai , Guokun Lai , Yiming Yang , Shinjae Yoo. With latent variables, stochastic recurrent models have achieved state-of-the-art performance in modeling sound-wave sequence. Density Estimation.David R. So, Wojciech Manke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V. Le´ Google Research, Brain Team {davidso, wojciechm, hanxiaol, zihangd, noam, qvl}@google.com Abstract Large Transformer models have been central to recent advances in natural language processing. The training and inference costs of these models, however, have grownHave you ever found yourself in a fashion emergency, desperately needing a last-minute alteration to your outfit? Whether it’s a hem that needs to be shortened, a dress that needs ...If your menstruation is usually on schedule and you are late by even one day, you might be pregnant, notes BabyCenter. However, it is rather common for women to be late in their pe...Zihang Dai, Hanxiao Liu, Quoc V Le, Mingxing Tan. Abstract. Transformers have attracted increasing interests in computer vision, but they still fall behind state-of-the-art convolutional networks.Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc V Le, and Ruslan Salakhutdinov. Transformer-xl: Attentive language models beyond a fixed-length context. arXiv preprint arXiv:1901.02860, 2019.

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That Qizhe Xie 1, 2, Zihang Dai , Eduard Hovy , Minh-Thang Luong , Quoc V. Le1 1 Google Research, Brain Team, 2 Carnegie Mellon University {qizhex, dzihang, hovy}@cs.cmu.edu, {thangluong, qvl}@google.com Abstract Semi-supervised learning lately has shown much promise in improving deep learn-ing models when labeled data is scarce.Zihang Dai. [email protected]. GitHub | Google Scholar. About me I'm a research scientist at Google Brain. I got my Ph.D. from the School of Computer Science at CMU.

How Conference Paper. Jun 2016. Zihang Dai. Lei Li. Wei Xu. How can we enable computers to automatically answer questions like "Who created the character Harry Potter"? Carefully built knowledge bases ...Authors. Hanxiao Liu, Zihang Dai, David So, Quoc V Le. Abstract. Transformers have become one of the most important architectural innovations in deep learning and have enabled many breakthroughs over the past few years.Author links open overlay panel Hieu Pham a 1, Zihang Dai a 1, Golnaz Ghiasi a 1, Kenji Kawaguchi b 1, Hanxiao Liu a, Adams Wei Yu a, Jiahui Yu a, Yi-Ting Chen a, Minh-Thang Luong a, Yonghui Wu a, Mingxing Tan a, Quoc V. Le a

When CoAtNet: marrying convolution and attention for all data sizes. Zihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan. December 2021NIPS '21: Proceedings of the 35th International Conference on Neural Information Processing Systems.Valentine’s Day is just around the corner, and it’s the perfect time to show your loved ones how much you care. But finding the right way to celebrate can be a challenge, especiall...…

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geogebra chrome extension Conference Paper. Jun 2016. Zihang Dai. Lei Li. Wei Xu. How can we enable computers to automatically answer questions like "Who created the character Harry Potter"? Carefully built knowledge bases ... evaaviolett leaksgail login Your wedding day is one of the most important events in your life, and you want to look your best. One way to ensure that you look sharp and stylish is by choosing the right tuxedo... mm filmelists ingrib hub Hieu Pham, Zihang Dai, Michael Qizhe Xie, Thang Luong, Quoc V Le. 25 Sep 2023. OpenReview Archive Direct Upload.Unsupervised Data Augmentation for Consistency Training. Qizhe Xie, Zihang Dai, Eduard Hovy, Minh-Thang Luong, Quoc V. Le. Semi-supervised learning lately has shown much promise in improving deep learning models when labeled data is scarce. Common among recent approaches is the use of consistency training on a large amount of unlabeled data to ... jasi jordan nudes May 27, 2017 · Good Semi-supervised Learning that Requires a Bad GAN. Zihang Dai, Zhilin Yang, Fan Yang, William W. Cohen, Ruslan Salakhutdinov. Semi-supervised learning methods based on generative adversarial networks (GANs) obtained strong empirical results, but it is not clear 1) how the discriminator benefits from joint training with a generator, and 2 ...Combiner: Full Attention Transformer with Sparse Computation Cost. Part of Advances in Neural Information Processing Systems 34 (NeurIPS 2021) Hongyu Ren, Hanjun Dai, Zihang Dai, Mengjiao Yang, Jure Leskovec, Dale Schuurmans, Bo Dai. Transformers provide a class of expressive architectures that are extremely effective for sequence modeling. lyna perez pussyjasi.bae leaked onlyfansmidcoastfcu Dai et al. (2021) Zihang Dai, Hanxiao Liu, Quoc V Le, and Mingxing Tan. Coatnet: Marrying convolution and attention for all data sizes. arXiv preprint arXiv:2106.04803, 2021. Devlin et al. (2018) Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. Bert: Pre-training of deep bidirectional transformers for language understanding.Author links open overlay panel Hieu Pham a 1, Zihang Dai a 1, Golnaz Ghiasi a 1, Kenji Kawaguchi b 1, Hanxiao Liu a, Adams Wei Yu a, Jiahui Yu a, Yi-Ting Chen a, Minh-Thang Luong a, Yonghui Wu a, Mingxing Tan a, Quoc V. Le a