Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox
Picture for Andrew M. Dai

Andrew M. Dai

PaLM: Scaling Language Modeling with Pathways



Aakanksha Chowdhery , Sharan Narang , Jacob Devlin , Maarten Bosma , Gaurav Mishra , Adam Roberts , Paul Barham , Hyung Won Chung , Charles Sutton , Sebastian Gehrmann , Parker Schuh , Kensen Shi , Sasha Tsvyashchenko , Joshua Maynez , Abhishek Rao , Parker Barnes , Yi Tay , Noam Shazeer , Vinodkumar Prabhakaran , Emily Reif , Nan Du , Ben Hutchinson , Reiner Pope , James Bradbury , Jacob Austin , Michael Isard , Guy Gur-Ari , Pengcheng Yin , Toju Duke , Anselm Levskaya , Sanjay Ghemawat , Sunipa Dev , Henryk Michalewski , Xavier Garcia , Vedant Misra , Kevin Robinson , Liam Fedus , Denny Zhou , Daphne Ippolito , David Luan , Hyeontaek Lim , Barret Zoph , Alexander Spiridonov , Ryan Sepassi , David Dohan , Shivani Agrawal , Mark Omernick , Andrew M. Dai , Thanumalayan Sankaranarayana Pillai , Marie Pellat , Aitor Lewkowycz , Erica Moreira , Rewon Child , Oleksandr Polozov , Katherine Lee , Zongwei Zhou , Xuezhi Wang , Brennan Saeta , Mark Diaz , Orhan Firat , Michele Catasta , Jason Wei , Kathy Meier-Hellstern , Douglas Eck , Jeff Dean , Slav Petrov , Noah Fiedel

Figure 1 for PaLM: Scaling Language Modeling with Pathways
Figure 2 for PaLM: Scaling Language Modeling with Pathways
Figure 3 for PaLM: Scaling Language Modeling with Pathways
Figure 4 for PaLM: Scaling Language Modeling with Pathways

   Access Paper or Ask Questions

Co-training Transformer with Videos and Images Improves Action Recognition



Bowen Zhang , Jiahui Yu , Christopher Fifty , Wei Han , Andrew M. Dai , Ruoming Pang , Fei Sha

Figure 1 for Co-training Transformer with Videos and Images Improves Action Recognition
Figure 2 for Co-training Transformer with Videos and Images Improves Action Recognition
Figure 3 for Co-training Transformer with Videos and Images Improves Action Recognition
Figure 4 for Co-training Transformer with Videos and Images Improves Action Recognition

   Access Paper or Ask Questions

GLaM: Efficient Scaling of Language Models with Mixture-of-Experts



Nan Du , Yanping Huang , Andrew M. Dai , Simon Tong , Dmitry Lepikhin , Yuanzhong Xu , Maxim Krikun , Yanqi Zhou , Adams Wei Yu , Orhan Firat , Barret Zoph , Liam Fedus , Maarten Bosma , Zongwei Zhou , Tao Wang , Yu Emma Wang , Kellie Webster , Marie Pellat , Kevin Robinson , Kathy Meier-Hellstern , Toju Duke , Lucas Dixon , Kun Zhang , Quoc V Le , Yonghui Wu , Zhifeng Chen , Claire Cui

Figure 1 for GLaM: Efficient Scaling of Language Models with Mixture-of-Experts
Figure 2 for GLaM: Efficient Scaling of Language Models with Mixture-of-Experts
Figure 3 for GLaM: Efficient Scaling of Language Models with Mixture-of-Experts
Figure 4 for GLaM: Efficient Scaling of Language Models with Mixture-of-Experts

   Access Paper or Ask Questions

Finetuned Language Models Are Zero-Shot Learners



Jason Wei , Maarten Bosma , Vincent Y. Zhao , Kelvin Guu , Adams Wei Yu , Brian Lester , Nan Du , Andrew M. Dai , Quoc V. Le

Figure 1 for Finetuned Language Models Are Zero-Shot Learners
Figure 2 for Finetuned Language Models Are Zero-Shot Learners
Figure 3 for Finetuned Language Models Are Zero-Shot Learners
Figure 4 for Finetuned Language Models Are Zero-Shot Learners

   Access Paper or Ask Questions

BEDS-Bench: Behavior of EHR-models under Distributional Shift--A Benchmark



Anand Avati , Martin Seneviratne , Emily Xue , Zhen Xu , Balaji Lakshminarayanan , Andrew M. Dai

Figure 1 for BEDS-Bench: Behavior of EHR-models under Distributional Shift--A Benchmark
Figure 2 for BEDS-Bench: Behavior of EHR-models under Distributional Shift--A Benchmark
Figure 3 for BEDS-Bench: Behavior of EHR-models under Distributional Shift--A Benchmark
Figure 4 for BEDS-Bench: Behavior of EHR-models under Distributional Shift--A Benchmark

   Access Paper or Ask Questions

MUFASA: Multimodal Fusion Architecture Search for Electronic Health Records



Zhen Xu , David R. So , Andrew M. Dai

Figure 1 for MUFASA: Multimodal Fusion Architecture Search for Electronic Health Records
Figure 2 for MUFASA: Multimodal Fusion Architecture Search for Electronic Health Records
Figure 3 for MUFASA: Multimodal Fusion Architecture Search for Electronic Health Records
Figure 4 for MUFASA: Multimodal Fusion Architecture Search for Electronic Health Records
* Accepted for publication at the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21) 
   Access Paper or Ask Questions

Learnability and Complexity of Quantum Samples



Murphy Yuezhen Niu , Andrew M. Dai , Li Li , Augustus Odena , Zhengli Zhao , Vadim Smelyanskyi , Hartmut Neven , Sergio Boixo

Figure 1 for Learnability and Complexity of Quantum Samples
Figure 2 for Learnability and Complexity of Quantum Samples
Figure 3 for Learnability and Complexity of Quantum Samples
Figure 4 for Learnability and Complexity of Quantum Samples

   Access Paper or Ask Questions

Training independent subnetworks for robust prediction



Marton Havasi , Rodolphe Jenatton , Stanislav Fort , Jeremiah Zhe Liu , Jasper Snoek , Balaji Lakshminarayanan , Andrew M. Dai , Dustin Tran

Figure 1 for Training independent subnetworks for robust prediction
Figure 2 for Training independent subnetworks for robust prediction
Figure 3 for Training independent subnetworks for robust prediction
Figure 4 for Training independent subnetworks for robust prediction

   Access Paper or Ask Questions

Learning Unstable Dynamical Systems with Time-Weighted Logarithmic Loss



Kamil Nar , Yuan Xue , Andrew M. Dai

Figure 1 for Learning Unstable Dynamical Systems with Time-Weighted Logarithmic Loss
Figure 2 for Learning Unstable Dynamical Systems with Time-Weighted Logarithmic Loss
Figure 3 for Learning Unstable Dynamical Systems with Time-Weighted Logarithmic Loss
Figure 4 for Learning Unstable Dynamical Systems with Time-Weighted Logarithmic Loss

   Access Paper or Ask Questions
1
2
3
4
>>