Quoc V. Le

ORCID

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 262

Top Venues

Publications

Tu Vu, Mohit Iyyer, Xuezhi Wang, Noah Constant, Jerry W. Wei, Jason Wei, Chris Tar, Yun-Hsuan Sung, Denny Zhou, Quoc V. Le, Thang Luong
FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation. ACL (Findings) (2024)
Zhecan Wang, Garrett Bingham, Adams Yu, Quoc V. Le, Thang Luong, Golnaz Ghiasi
HaloQuest: A Visual Hallucination Dataset for Advancing Multimodal Reasoning. CoRR (2024)
Bradley C. A. Brown, Jordan Juravsky, Ryan Saul Ehrlich, Ronald Clark, Quoc V. Le, Christopher Ré, Azalia Mirhoseini
Large Language Monkeys: Scaling Inference Compute with Repeated Sampling. CoRR (2024)
Xiao Ma, Swaroop Mishra, Ariel Liu, Sophie Ying Su, Jilin Chen, Chinmay Kulkarni, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi
Beyond ChatBots: ExploreLLM for Structured Thoughts and Personalized Model Responses. CHI Extended Abstracts (2024)
Pei Zhou, Jay Pujara, Xiang Ren, Xinyun Chen, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou, Swaroop Mishra, Huaixiu Steven Zheng
Self-Discover: Large Language Models Self-Compose Reasoning Structures. CoRR (2024)
Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V. Le, Denny Zhou, Xinyun Chen
Large Language Models as Optimizers. ICLR (2024)
Jerry Wei, Chengrun Yang, Xinying Song, Yifeng Lu, Nathan Hu, Dustin Tran, Daiyi Peng, Ruibo Liu, Da Huang, Cosmo Du, Quoc V. Le
Long-form factuality in large language models. CoRR (2024)
Trieu H. Trinh, Yuhuai Wu, Quoc V. Le, He He, Thang Luong
Solving olympiad geometry without human demonstrations. Nat. 625 (7995) (2024)
Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, Heng-Tze Cheng, Ed H. Chi, Quoc V. Le, Denny Zhou
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models. ICLR (2024)
Huaixiu Steven Zheng, Swaroop Mishra, Hugh Zhang, Xinyun Chen, Minmin Chen, Azade Nova, Le Hou, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou
NATURAL PLAN: Benchmarking LLMs on Natural Language Planning. CoRR (2024)
Jordan Dotzel, Gang Wu, Andrew Li, Muhammad Umar, Yun Ni, Mohamed S. Abdelfattah, Zhiru Zhang, Liqun Cheng, Martin G. Dixon, Norman P. Jouppi, Quoc V. Le, Sheng Li
FLIQS: One-Shot Mixed-Precision Floating-Point and Integer Quantization Search. CoRR (2023)
Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V. Le, Denny Zhou, Xinyun Chen
Large Language Models as Optimizers. CoRR (2023)
Mirac Suzgun, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V. Le, Ed Chi, Denny Zhou, Jason Wei
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them. ACL (Findings) (2023)
Jerry W. Wei, Le Hou, Andrew K. Lampinen, Xiangning Chen, Da Huang, Yi Tay, Xinyun Chen, Yifeng Lu, Denny Zhou, Tengyu Ma, Quoc V. Le
Symbol tuning improves in-context learning in language models. EMNLP (2023)
Sang Michael Xie, Hieu Pham, Xuanyi Dong, Nan Du, Hanxiao Liu, Yifeng Lu, Percy S. Liang, Quoc V. Le, Tengyu Ma, Adams Wei Yu
DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining. NeurIPS (2023)
Jerry W. Wei, Da Huang, Yifeng Lu, Denny Zhou, Quoc V. Le
Simple synthetic data reduces sycophancy in large language models. CoRR (2023)
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, Denny Zhou
Self-Consistency Improves Chain of Thought Reasoning in Language Models. ICLR (2023)
Sheng Li, Garrett Andersen, Tao Chen, Liqun Cheng, Julian Grady, Da Huang, Quoc V. Le, Andrew Li, Xin Li, Yang Li, Chen Liang, Yifeng Lu, Yun Ni, Ruoming Pang, Mingxing Tan, Martin Wicke, Gang Wu, Shengqi Zhu, Parthasarathy Ranganathan, Norman P. Jouppi
Hyperscale Hardware Optimized Neural Architecture Search. ASPLOS (3) (2023)
Esteban Real, Yao Chen, Mirko Rossini, Connal de Souza, Manav Garg, Akhil Verghese, Moritz Firsching, Quoc V. Le, Ekin Dogus Cubuk, David H. Park
AutoNumerics-Zero: Automated Discovery of State-of-the-Art Mathematical Functions. CoRR (2023)
Xiangning Chen, Chen Liang, Da Huang, Esteban Real, Kaiyuan Wang, Hieu Pham, Xuanyi Dong, Thang Luong, Cho-Jui Hsieh, Yifeng Lu, Quoc V. Le
Symbolic Discovery of Optimization Algorithms. NeurIPS (2023)
Daiyi Peng, Xuanyi Dong, Esteban Real, Yifeng Lu, Quoc V. Le
PyGlove: Efficiently Exchanging ML Ideas as Code. CoRR (2023)
Qingqing Huang, Daniel S. Park, Tao Wang, Timo I. Denk, Andy Ly, Nanxin Chen, Zhengdong Zhang, Zhishuai Zhang, Jiahui Yu, Christian Havnø Frank, Jesse H. Engel, Quoc V. Le, William Chan, Wei Han
Noise2Music: Text-conditioned Music Generation with Diffusion Models. CoRR (2023)
Yanqi Zhou, Nan Du, Yanping Huang, Daiyi Peng, Chang Lan, Da Huang, Siamak Shakeri, David R. So, Andrew M. Dai, Yifeng Lu, Zhifeng Chen, Quoc V. Le, Claire Cui, James Laudon, Jeff Dean
Brainformers: Trading Simplicity for Efficiency. ICML (2023)
Yanqi Zhou, Nan Du, Yanping Huang, Daiyi Peng, Chang Lan, Da Huang, Siamak Shakeri, David R. So, Andrew M. Dai, Yifeng Lu, Zhifeng Chen, Quoc V. Le, Claire Cui, James Laudon, Jeff Dean
Brainformers: Trading Simplicity for Efficiency. CoRR (2023)
Sang Michael Xie, Hieu Pham, Xuanyi Dong, Nan Du, Hanxiao Liu, Yifeng Lu, Percy Liang, Quoc V. Le, Tengyu Ma, Adams Wei Yu
DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining. CoRR (2023)
Shayne Longpre, Le Hou, Tu Vu, Albert Webson, Hyung Won Chung, Yi Tay, Denny Zhou, Quoc V. Le, Barret Zoph, Jason Wei, Adam Roberts
The Flan Collection: Designing Data and Methods for Effective Instruction Tuning. ICML (2023)
Jerry W. Wei, Le Hou, Andrew Lampinen, Xiangning Chen, Da Huang, Yi Tay, Xinyun Chen, Yifeng Lu, Denny Zhou, Tengyu Ma, Quoc V. Le
Symbol tuning improves in-context learning in language models. CoRR (2023)
Ryan Gillard, Stephen Jonany, Yingjie Miao, Michael Munn, Connal de Souza, Jonathan Dungay, Chen Liang, David R. So, Quoc V. Le, Esteban Real
Unified Functional Hashing in Automatic Machine Learning. CoRR (2023)
Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V. Le, Ed H. Chi
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. ICLR (2023)
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)
Tu Vu, Mohit Iyyer, Xuezhi Wang, Noah Constant, Jerry W. Wei, Jason Wei, Chris Tar, Yun-Hsuan Sung, Denny Zhou, Quoc V. Le, Thang Luong
FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation. CoRR (2023)
Xiangning Chen, Chen Liang, Da Huang, Esteban Real, Kaiyuan Wang, Yao Liu, Hieu Pham, Xuanyi Dong, Thang Luong, Cho-Jui Hsieh, Yifeng Lu, Quoc V. Le
Symbolic Discovery of Optimization Algorithms. CoRR (2023)
Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, Heng-Tze Cheng, Ed H. Chi, Quoc V. Le, Denny Zhou
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models. CoRR (2023)
Shayne Longpre, Le Hou, Tu Vu, Albert Webson, Hyung Won Chung, Yi Tay, Denny Zhou, Quoc V. Le, Barret Zoph, Jason Wei, Adam Roberts
The Flan Collection: Designing Data and Methods for Effective Instruction Tuning. CoRR (2023)
Mirac Suzgun, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V. Le, Ed H. Chi, Denny Zhou, Jason Wei
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them. CoRR (2022)
Weizhe Hua, Zihang Dai, Hanxiao Liu, Quoc V. Le
Transformer Quality in Linear Time. CoRR (2022)
Yanqi Zhou, Tao Lei, Hanxiao Liu, Nan Du, Yanping Huang, Vincent Zhao, Andrew M. Dai, Zhifeng Chen, Quoc V. Le, James Laudon
Mixture-of-Experts with Expert Choice Routing. NeurIPS (2022)
David A. Patterson, Joseph Gonzalez, Urs Hölzle, Quoc V. Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, Jeff Dean
The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink. CoRR (2022)
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Y. Zhao, Yanping Huang, Andrew M. Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, Jason Wei
Scaling Instruction-Finetuned Language Models. CoRR (2022)
Yingwei Li, Adams Wei Yu, Tianjian Meng, Benjamin Caine, Jiquan Ngiam, Daiyi Peng, Junyang Shen, Bo Wu, Yifeng Lu, Denny Zhou, Quoc V. Le, Alan L. Yuille, Mingxing Tan
DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection. CoRR (2022)
Yingwei Li, Adams Wei Yu, Tianjian Meng, Benjamin Caine, Jiquan Ngiam, Daiyi Peng, Junyang Shen, Yifeng Lu, Denny Zhou, Quoc V. Le, Alan L. Yuille, Mingxing Tan
DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection. CVPR (2022)
David A. Patterson, Joseph Gonzalez, Urs Hölzle, Quoc V. Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, Jeff Dean
The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink. Computer 55 (7) (2022)
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 P. Bosma, Zongwei Zhou, Tao Wang, Yu Emma Wang, Kellie Webster, Marie Pellat, Kevin Robinson, Kathleen S. Meier-Hellstern, Toju Duke, Lucas Dixon, Kun Zhang, Quoc V. Le, Yonghui Wu, Zhifeng Chen, Claire Cui
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts. ICML (2022)
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Denny Zhou
Rationale-Augmented Ensembles in Language Models. CoRR (2022)
Yu Zhang, Daniel S. Park, Wei Han, James Qin, Anmol Gulati, Joel Shor, Aren Jansen, Yuanzhong Xu, Yanping Huang, Shibo Wang, Zongwei Zhou, Bo Li, Min Ma, William Chan, Jiahui Yu, Yongqiang Wang, Liangliang Cao, Khe Chai Sim, Bhuvana Ramabhadran, Tara N. Sainath, Françoise Beaufays, Zhifeng Chen, Quoc V. Le, Chung-Cheng Chiu, Ruoming Pang, Yonghui Wu
BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition. IEEE J. Sel. Top. Signal Process. 16 (6) (2022)
Chengrun Yang, Gabriel Bender, Hanxiao Liu, Pieter-Jan Kindermans, Madeleine Udell, Yifeng Lu, Quoc V. Le, Da Huang
TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets. NeurIPS (2022)
Gary Wang, Ekin D. Cubuk, Andrew Rosenberg, Shuyang Cheng, Ron J. Weiss, Bhuvana Ramabhadran, Pedro J. Moreno, Quoc V. Le, Daniel S. Park
G-Augment: Searching for the Meta-Structure of Data Augmentation Policies for ASR. SLT (2022)
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, Denny Zhou
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. NeurIPS (2022)
Dan Zhang, Safeen Huda, Ebrahim M. Songhori, Kartik Prabhu, Quoc V. Le, Anna Goldie, Azalia Mirhoseini
A full-stack search technique for domain optimized deep learning accelerators. ASPLOS (2022)
Gary Wang, Ekin D. Cubuk, Andrew Rosenberg, Shuyang Cheng, Ron J. Weiss, Bhuvana Ramabhadran, Pedro J. Moreno, Quoc V. Le, Daniel S. Park
G-Augment: Searching for the Meta-Structure of Data Augmentation Policies for ASR. CoRR (2022)
Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, Quoc V. Le
Finetuned Language Models are Zero-Shot Learners. ICLR (2022)
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Denny Zhou
Self-Consistency Improves Chain of Thought Reasoning in Language Models. CoRR (2022)
Yi Tay, Jason Wei, Hyung Won Chung, Vinh Q. Tran, David R. So, Siamak Shakeri, Xavier Garcia, Huaixiu Steven Zheng, Jinfeng Rao, Aakanksha Chowdhery, Denny Zhou, Donald Metzler, Slav Petrov, Neil Houlsby, Quoc V. Le, Mostafa Dehghani
Transcending Scaling Laws with 0.1% Extra Compute. CoRR (2022)
Chengrun Yang, Gabriel Bender, Hanxiao Liu, Pieter-Jan Kindermans, Madeleine Udell, Yifeng Lu, Quoc V. Le, Da Huang
Resource-Constrained Neural Architecture Search on Tabular Datasets. CoRR (2022)
Jason Wei, Yi Tay, Quoc V. Le
Inverse scaling can become U-shaped. CoRR (2022)
Weizhe Hua, Zihang Dai, Hanxiao Liu, Quoc V. Le
Transformer Quality in Linear Time. ICML (2022)
Tianjian Meng, Golnaz Ghiasi, Reza Mahjourian, Quoc V. Le, Mingxing Tan
Revisiting Multi-Scale Feature Fusion for Semantic Segmentation. CoRR (2022)
Arissa Wongpanich, Hieu Pham, James Demmel, Mingxing Tan, Quoc V. Le, Yang You, Sameer Kumar
Training EfficientNets at Supercomputer Scale: 83% ImageNet Top-1 Accuracy in One Hour. IPDPS Workshops (2021)
John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Sergey Levine, Quoc V. Le, Honglak Lee, Aleksandra Faust
Evolving Reinforcement Learning Algorithms. CoRR (2021)
Hanxiao Liu, Zihang Dai, David R. So, Quoc V. Le
Pay Attention to MLPs. NeurIPS (2021)
Tu Vu, Minh-Thang Luong, Quoc V. Le, Grady Simon, Mohit Iyyer
STraTA: Self-Training with Task Augmentation for Better Few-shot Learning. EMNLP (1) (2021)
John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V. Le, Sergey Levine, Honglak Lee, Aleksandra Faust
Evolving Reinforcement Learning Algorithms. ICLR (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)
Mingxing Tan, Quoc V. Le
EfficientNetV2: Smaller Models and Faster Training. CoRR (2021)
Mingxing Tan, Quoc V. Le
EfficientNetV2: Smaller Models and Faster Training. ICML (2021)
Hieu Pham, Zihang Dai, Qizhe Xie, Quoc V. Le
Meta Pseudo Labels. CVPR (2021)
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
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts. CoRR (2021)
Dan Zhang, Safeen Huda, Ebrahim M. Songhori, Quoc V. Le, Anna Goldie, Azalia Mirhoseini
A Full-stack Accelerator Search Technique for Vision Applications. CoRR (2021)
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc V. Le, Yun-Hsuan Sung, Zhen Li, Tom Duerig
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision. ICML (2021)
Jacob Austin, Augustus Odena, Maxwell Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie J. Cai, Michael Terry, Quoc V. Le, Charles Sutton
Program Synthesis with Large Language Models. CoRR (2021)
Vikas Verma, Thang Luong, Kenji Kawaguchi, Hieu Pham, Quoc V. Le
Towards Domain-Agnostic Contrastive Learning. ICML (2021)
David A. Patterson, Joseph Gonzalez, Quoc V. Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, Jeff Dean
Carbon Emissions and Large Neural Network Training. CoRR (2021)
Yu Zhang, Daniel S. Park, Wei Han, James Qin, Anmol Gulati, Joel Shor, Aren Jansen, Yuanzhong Xu, Yanping Huang, Shibo Wang, Zongwei Zhou, Bo Li, Min Ma, William Chan, Jiahui Yu, Yongqiang Wang, Liangliang Cao, Khe Chai Sim, Bhuvana Ramabhadran, Tara N. Sainath, Françoise Beaufays, Zhifeng Chen, Quoc V. Le, Chung-Cheng Chiu, Ruoming Pang, Yonghui Wu
BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition. CoRR (2021)
Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, Quoc V. Le
Finetuned Language Models Are Zero-Shot Learners. CoRR (2021)
William Chan, Daniel S. Park, Chris A. Lee, Yu Zhang, Quoc V. Le, Mohammad Norouzi
SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network. CoRR (2021)
Zihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan
CoAtNet: Marrying Convolution and Attention for All Data Sizes. CoRR (2021)
Sheng Li, Mingxing Tan, Ruoming Pang, Andrew Li, Liqun Cheng, Quoc V. Le, Norman P. Jouppi
Searching for Fast Model Families on Datacenter Accelerators. CVPR (2021)
Hanxiao Liu, Zihang Dai, David R. So, Quoc V. Le
Pay Attention to MLPs. CoRR (2021)
Sheng Li, Mingxing Tan, Ruoming Pang, Andrew Li, Liqun Cheng, Quoc V. Le, Norman P. Jouppi
Searching for Fast Model Families on Datacenter Accelerators. 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)
Golnaz Ghiasi, Barret Zoph, Ekin D. Cubuk, Quoc V. Le, Tsung-Yi Lin
Multi-Task Self-Training for Learning General Representations. ICCV (2021)
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc V. Le, Yun-Hsuan Sung, Zhen Li, Tom Duerig
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision. CoRR (2021)
Azalia Mirhoseini, Anna Goldie, Mustafa Yazgan, Joe Wenjie Jiang, Ebrahim M. Songhori, Shen Wang, Young-Joon Lee, Eric Johnson, Omkar Pathak, Azade Nazi, Jiwoo Pak, Andy Tong, Kavya Srinivasa, William Hang, Emre Tuncer, Quoc V. Le, James Laudon, Richard Ho, Roger Carpenter, Jeff Dean
A graph placement methodology for fast chip design. Nat. 594 (7862) (2021)
Hieu Pham, Quoc V. Le
AutoDropout: Learning Dropout Patterns to Regularize Deep Networks. AAAI (2021)
Daiyi Peng, Xuanyi Dong, Esteban Real, Mingxing Tan, Yifeng Lu, Hanxiao Liu, Gabriel Bender, Adam Kraft, Chen Liang, Quoc V. Le
PyGlove: Symbolic Programming for Automated Machine Learning. CoRR (2021)
Tu Vu, Minh-Thang Luong, Quoc V. Le, Grady Simon, Mohit Iyyer
STraTA: Self-Training with Task Augmentation for Better Few-shot Learning. CoRR (2021)
Golnaz Ghiasi, Yin Cui, Aravind Srinivas, Rui Qian, Tsung-Yi Lin, Ekin D. Cubuk, Quoc V. Le, Barret Zoph
Simple Copy-Paste Is a Strong Data Augmentation Method for Instance Segmentation. CVPR (2021)
David R. So, Wojciech Manke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V. Le
Searching for Efficient Transformers for Language Modeling. NeurIPS (2021)
Hieu Pham, Quoc V. Le
AutoDropout: Learning Dropout Patterns to Regularize Deep Networks. CoRR (2021)
Golnaz Ghiasi, Barret Zoph, Ekin D. Cubuk, Quoc V. Le, Tsung-Yi Lin
Multi-Task Self-Training for Learning General Representations. CoRR (2021)
Hanxiao Liu, Andrew Brock, Karen Simonyan, Quoc V. Le
Evolving Normalization-Activation Layers. CoRR (2020)
Bo Chen, Golnaz Ghiasi, Hanxiao Liu, Tsung-Yi Lin, Dmitry Kalenichenko, Hartwig Adam, Quoc V. Le
MnasFPN: Learning Latency-Aware Pyramid Architecture for Object Detection on Mobile Devices. CVPR (2020)
Kevin Clark, Minh-Thang Luong, Quoc V. Le, Christopher D. Manning
Pre-Training Transformers as Energy-Based Cloze Models. EMNLP (1) (2020)
Kevin Clark, Minh-Thang Luong, Quoc V. Le, Christopher D. Manning
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators. CoRR (2020)
Xinyun Chen, Chen Liang, Adams Wei Yu, Denny Zhou, Dawn Song, Quoc V. Le
Neural Symbolic Reader: Scalable Integration of Distributed and Symbolic Representations for Reading Comprehension. ICLR (2020)
Cihang Xie, Mingxing Tan, Boqing Gong, Alan L. Yuille, Quoc V. Le
Smooth Adversarial Training. CoRR (2020)
Yu Zhang, James Qin, Daniel S. Park, Wei Han, Chung-Cheng Chiu, Ruoming Pang, Quoc V. Le, Yonghui Wu
Pushing the Limits of Semi-Supervised Learning for Automatic Speech Recognition. CoRR (2020)
Daniel S. Park, Yu Zhang, Chung-Cheng Chiu, Youzheng Chen, Bo Li, William Chan, Quoc V. Le, Yonghui Wu
Specaugment on Large Scale Datasets. ICASSP (2020)
Shuyang Cheng, Zhaoqi Leng, Ekin Dogus Cubuk, Barret Zoph, Chunyan Bai, Jiquan Ngiam, Yang Song, Benjamin Caine, Vijay Vasudevan, Congcong Li, Quoc V. Le, Jonathon Shlens, Dragomir Anguelov
Improving 3D Object Detection Through Progressive Population Based Augmentation. ECCV (21) (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Quoc V. Le