Le, Quoc V.

91 publications

ICML 2025 EVOLvE: Evaluating and Optimizing LLMs for In-Context Exploration Allen Nie, Yi Su, Bo Chang, Jonathan Lee, Ed H. Chi, Quoc V Le, Minmin Chen

JMLR 2025 Gold-Medalist Performance in Solving Olympiad Geometry with AlphaGeometry2 Yuri Chervonyi, Trieu H. Trinh, Miroslav Olšák, Xiaomeng Yang, Hoang H. Nguyen, Marcelo Menegali, Junehyuk Jung, Junsu Kim, Vikas Verma, Quoc V. Le, Thang Luong

ICML 2025 Reward-Guided Prompt Evolving in Reinforcement Learning for LLMs Ziyu Ye, Rishabh Agarwal, Tianqi Liu, Rishabh Joshi, Sarmishta Velury, Quoc V Le, Qijun Tan, Yuan Liu

ICML 2025 SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-Training Tianzhe Chu, Yuexiang Zhai, Jihan Yang, Shengbang Tong, Saining Xie, Dale Schuurmans, Quoc V Le, Sergey Levine, Yi Ma

NeurIPSW 2024 Evolving Alignment via Asymmetric Self-Play Ziyu Ye, Rishabh Agarwal, Tianqi Liu, Rishabh Joshi, Sarmishta Velury, Quoc V Le, Qijun Tan, Yuan Liu

AutoML 2024 FLIQS: One-Shot Mixed-Precision Floating-Point and Integer Quantization Search 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

ECCV 2024 HaloQuest: A Visual Hallucination Dataset for Advancing Multimodal Reasoning Zhecan Wang, Garrett Bingham, Adams Wei Yu, Quoc V. Le, Thang Luong, Golnaz Ghiasi

ICLR 2024 Large Language Models as Optimizers Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V Le, Denny Zhou, Xinyun Chen

NeurIPS 2024 Long-Form Factuality in Large Language Models Jerry Wei, Chengrun Yang, Xinying Song, Yifeng Lu, Nathan Hu, Jie Huang, Dustin Tran, Daiyi Peng, Ruibo Liu, Da Huang, Cosmo Du, Quoc V. Le

NeurIPS 2024 SELF-DISCOVER: Large Language Models Self-Compose Reasoning Structures Pei Zhou, Jay Pujara, Xiang Ren, Xinyun Chen, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou, Swaroop Mishra, Huaixiu Steven Zheng

JMLR 2024 Scaling Instruction-Finetuned Language Models Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Alex Castro-Ros, Marie Pellat, Kevin Robinson, Dasha Valter, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Zhao, Yanping Huang, Andrew Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, Jason Wei

ICLR 2024 Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, Heng-Tze Cheng, Ed H. Chi, Quoc V Le, Denny Zhou

ICML 2023 Brainformers: Trading Simplicity for Efficiency Yanqi Zhou, Nan Du, Yanping Huang, Daiyi Peng, Chang Lan, Da Huang, Siamak Shakeri, David So, Andrew M. Dai, Yifeng Lu, Zhifeng Chen, Quoc V Le, Claire Cui, James Laudon, Jeff Dean

NeurIPS 2023 DoReMi: Optimizing Data Mixtures Speeds up Language Model Pretraining Sang Michael Xie, Hieu Pham, Xuanyi Dong, Nan Du, Hanxiao Liu, Yifeng Lu, Percy Liang, Quoc V Le, Tengyu Ma, Adams Wei Yu

ICLR 2023 Least-to-Most Prompting Enables Complex Reasoning in Large Language Models Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V Le, Ed H. Chi

ICLR 2023 Self-Consistency Improves Chain of Thought Reasoning in Language Models Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, Denny Zhou

NeurIPS 2023 Symbolic Discovery of Optimization Algorithms Xiangning Chen, Chen Liang, Da Huang, Esteban Real, Kaiyuan Wang, Hieu Pham, Xuanyi Dong, Thang Luong, Cho-Jui Hsieh, Yifeng Lu, Quoc V Le

ICML 2023 The FLAN Collection: Designing Data and Methods for Effective Instruction Tuning Shayne Longpre, Le Hou, Tu Vu, Albert Webson, Hyung Won Chung, Yi Tay, Denny Zhou, Quoc V Le, Barret Zoph, Jason Wei, Adam Roberts

NeurIPS 2022 Chain-of-Thought Prompting Elicits Reasoning in Large Language Models Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou

CVPR 2022 DeepFusion: LiDAR-Camera Deep Fusion for Multi-Modal 3D Object Detection Yingwei Li, Adams Wei Yu, Tianjian Meng, Ben Caine, Jiquan Ngiam, Daiyi Peng, Junyang Shen, Yifeng Lu, Denny Zhou, Quoc V. Le, Alan Yuille, Mingxing Tan

ICLR 2022 Finetuned Language Models Are Zero-Shot Learners Jason Wei, Maarten Bosma, Vincent Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, Quoc V Le

NeurIPS 2022 Mixture-of-Experts with Expert Choice Routing Yanqi Zhou, Tao Lei, Hanxiao Liu, Nan Du, Yanping Huang, Vincent Zhao, Andrew M Dai, Zhifeng Chen, Quoc V Le, James Laudon

NeurIPS 2022 TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets Chengrun Yang, Gabriel Bender, Hanxiao Liu, Pieter-Jan Kindermans, Madeleine Udell, Yifeng Lu, Quoc V Le, Da Huang

AAAI 2021 AutoDropout: Learning Dropout Patterns to Regularize Deep Networks Hieu Pham, Quoc V. Le

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

ICLR 2021 Evolving Reinforcement Learning Algorithms John D Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V Le, Sergey Levine, Honglak Lee, Aleksandra Faust

CVPR 2021 Meta Pseudo Labels Hieu Pham, Zihang Dai, Qizhe Xie, Quoc V. Le

ICCV 2021 Multi-Task Self-Training for Learning General Representations Golnaz Ghiasi, Barret Zoph, Ekin D. Cubuk, Quoc V. Le, Tsung-Yi Lin

NeurIPS 2021 Pay Attention to MLPs Hanxiao Liu, Zihang Dai, David So, Quoc V Le

NeurIPS 2021 Searching for Efficient Transformers for Language Modeling David So, Wojciech Mańke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V Le

CVPR 2021 Searching for Fast Model Families on Datacenter Accelerators Sheng Li, Mingxing Tan, Ruoming Pang, Andrew Li, Liqun Cheng, Quoc V. Le, Norman P. Jouppi

CVPR 2021 Simple Copy-Paste Is a Strong Data Augmentation Method for Instance Segmentation Golnaz Ghiasi, Yin Cui, Aravind Srinivas, Rui Qian, Tsung-Yi Lin, Ekin D. Cubuk, Quoc V. Le, Barret Zoph

ICLR 2020 ELECTRA: Pre-Training Text Encoders as Discriminators Rather than Generators Kevin Clark, Minh-Thang Luong, Quoc V. Le, Christopher D. Manning

NeurIPS 2020 Evolving Normalization-Activation Layers Hanxiao Liu, Andy Brock, Karen Simonyan, Quoc V. Le

NeurIPS 2020 Funnel-Transformer: Filtering Out Sequential Redundancy for Efficient Language Processing Zihang Dai, Guokun Lai, Yiming Yang, Quoc V. Le

ECCV 2020 Improving 3D Object Detection Through Progressive Population Based Augmentation 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

ECCV 2020 Learning Data Augmentation Strategies for Object Detection Barret Zoph, Ekin D. Cubuk, Golnaz Ghiasi, Tsung-Yi Lin, Jonathon Shlens, Quoc V. Le

ICLR 2020 Neural Symbolic Reader: Scalable Integration of Distributed and Symbolic Representations for Reading Comprehension Xinyun Chen, Chen Liang, Adams Wei Yu, Denny Zhou, Dawn Song, Quoc V. Le

NeurIPS 2020 PyGlove: Symbolic Programming for Automated Machine Learning Daiyi Peng, Xuanyi Dong, Esteban Real, Mingxing Tan, Yifeng Lu, Gabriel Bender, Hanxiao Liu, Adam Kraft, Chen Liang, Quoc V. Le

NeurIPS 2020 RandAugment: Practical Automated Data Augmentation with a Reduced Search Space Ekin Dogus Cubuk, Barret Zoph, Jon Shlens, Quoc V. Le

CVPRW 2020 Randaugment: Practical Automated Data Augmentation with a Reduced Search Space Ekin D. Cubuk, Barret Zoph, Jonathon Shlens, Quoc V. Le

NeurIPS 2020 Rethinking Pre-Training and Self-Training Barret Zoph, Golnaz Ghiasi, Tsung-Yi Lin, Yin Cui, Hanxiao Liu, Ekin Dogus Cubuk, Quoc V. Le

NeurIPS 2020 Unsupervised Data Augmentation for Consistency Training Qizhe Xie, Zihang Dai, Eduard Hovy, Thang Luong, Quoc V. Le

NeurIPS 2019 CondConv: Conditionally Parameterized Convolutions for Efficient Inference Brandon Yang, Gabriel Bender, Quoc V Le, Jiquan Ngiam

ICLR 2019 Diversity and Depth in Per-Example Routing Models Prajit Ramachandran, Quoc V. Le

NeurIPS 2019 GPipe: Efficient Training of Giant Neural Networks Using Pipeline Parallelism Yanping Huang, Youlong Cheng, Ankur Bapna, Orhan Firat, Dehao Chen, Mia Chen, HyoukJoong Lee, Jiquan Ngiam, Quoc V Le, Yonghui Wu, Zhifeng Chen

NeurIPS 2019 High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V Le, Honglak Lee

NeurIPS 2019 Mixtape: Breaking the SoftMax Bottleneck Efficiently Zhilin Yang, Thang Luong, Ruslan Salakhutdinov, Quoc V Le

AAAI 2019 Regularized Evolution for Image Classifier Architecture Search Esteban Real, Alok Aggarwal, Yanping Huang, Quoc V. Le

NeurIPS 2019 Saccader: Improving Accuracy of Hard Attention Models for Vision Gamaleldin Elsayed, Simon Kornblith, Quoc V Le

NeurIPS 2019 XLNet: Generalized Autoregressive Pretraining for Language Understanding Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, Quoc V Le

ICLR 2018 A Hierarchical Model for Device Placement Azalia Mirhoseini, Anna Goldie, Hieu Pham, Benoit Steiner, Quoc V. Le, Jeff Dean

ICLR 2018 Don't Decay the Learning Rate, Increase the Batch Size Samuel L. Smith, Pieter-Jan Kindermans, Chris Ying, Quoc V. Le

NeurIPS 2018 DropBlock: A Regularization Method for Convolutional Networks Golnaz Ghiasi, Tsung-Yi Lin, Quoc V Le

NeurIPS 2018 Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing Chen Liang, Mohammad Norouzi, Jonathan Berant, Quoc V Le, Ni Lao

ICLR 2018 QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension Adams Wei Yu, David Dohan, Minh-Thang Luong, Rui Zhao, Kai Chen, Mohammad Norouzi, Quoc V. Le

ICML 2017 Device Placement Optimization with Reinforcement Learning Azalia Mirhoseini, Hieu Pham, Quoc V. Le, Benoit Steiner, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Mohammad Norouzi, Samy Bengio, Jeff Dean

ICLR 2017 HyperNetworks David Ha, Andrew M. Dai, Quoc V. Le

ICML 2017 Large-Scale Evolution of Image Classifiers Esteban Real, Sherry Moore, Andrew Selle, Saurabh Saxena, Yutaka Leon Suematsu, Jie Tan, Quoc V. Le, Alexey Kurakin

ICLR 2017 Latent Sequence Decompositions William Chan, Yu Zhang, Quoc V. Le, Navdeep Jaitly

ICLR 2017 Learning a Natural Language Interface with Neural Programmer Arvind Neelakantan, Quoc V. Le, Martín Abadi, Andrew McCallum, Dario Amodei

ICLR 2017 Neural Architecture Search with Reinforcement Learning Barret Zoph, Quoc V. Le

ICLR 2017 Neural Combinatorial Optimization with Reinforcement Learning Irwan Bello, Hieu Pham, Quoc V. Le, Mohammad Norouzi, Samy Bengio

ICML 2017 Neural Optimizer Search with Reinforcement Learning Irwan Bello, Barret Zoph, Vijay Vasudevan, Quoc V. Le

ICLR 2017 Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc V. Le, Geoffrey E. Hinton, Jeff Dean

NeurIPS 2016 An Online Sequence-to-Sequence Model Using Partial Conditioning Navdeep Jaitly, Quoc V Le, Oriol Vinyals, Ilya Sutskever, David Sussillo, Samy Bengio

ICLR 2016 Multi-Task Sequence to Sequence Learning Minh-Thang Luong, Quoc V. Le, Ilya Sutskever, Oriol Vinyals, Lukasz Kaiser

ICLR 2016 Neural Programmer: Inducing Latent Programs with Gradient Descent Arvind Neelakantan, Quoc V. Le, Ilya Sutskever

NeurIPS 2015 Semi-Supervised Sequence Learning Andrew M Dai, Quoc V Le

NeurIPS 2014 Sequence to Sequence Learning with Neural Networks Ilya Sutskever, Oriol Vinyals, Quoc V Le

ICML 2012 Building High-Level Features Using Large Scale Unsupervised Learning Quoc V. Le, Marc'Aurelio Ranzato, Rajat Monga, Matthieu Devin, Greg Corrado, Kai Chen, Jeffrey Dean, Andrew Y. Ng

NeurIPS 2012 Large Scale Distributed Deep Networks Jeffrey Dean, Greg Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Mark Mao, Marc'aurelio Ranzato, Andrew Senior, Paul Tucker, Ke Yang, Quoc V. Le, Andrew Y. Ng

NeurIPS 2011 ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning Quoc V. Le, Alexandre Karpenko, Jiquan Ngiam, Andrew Y. Ng

CVPR 2011 Learning Hierarchical Invariant Spatio-Temporal Features for Action Recognition with Independent Subspace Analysis Quoc V. Le, Will Y. Zou, Serena Y. Yeung, Andrew Y. Ng

ICML 2011 On Optimization Methods for Deep Learning Quoc V. Le, Jiquan Ngiam, Adam Coates, Ahbik Lahiri, Bobby Prochnow, Andrew Y. Ng

JMLR 2010 Bundle Methods for Regularized Risk Minimization Choon Hui Teo, S.V.N. Vishwanthan, Alex J. Smola, Quoc V. Le

NeurIPS 2010 Tiled Convolutional Neural Networks Jiquan Ngiam, Zhenghao Chen, Daniel Chia, Pang W. Koh, Quoc V. Le, Andrew Y. Ng

JMLR 2009 Estimating Labels from Label Proportions Novi Quadrianto, Alex J. Smola, Tibério S. Caetano, Quoc V. Le

NeurIPS 2009 Measuring Invariances in Deep Networks Ian Goodfellow, Honglak Lee, Quoc V. Le, Andrew Saxe, Andrew Y. Ng

ICML 2009 Proximal Regularization for Online and Batch Learning Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo

ICML 2008 Estimating Labels from Label Proportions Novi Quadrianto, Alexander J. Smola, Tibério S. Caetano, Quoc V. Le

NeurIPS 2008 Tighter Bounds for Structured Estimation Olivier Chapelle, Chuong B. Do, Choon H. Teo, Quoc V. Le, Alex J. Smola

NeurIPS 2007 Bundle Methods for Machine Learning Quoc V. Le, Alex J. Smola, S.v.n. Vishwanathan

NeurIPS 2007 COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking Markus Weimer, Alexandros Karatzoglou, Quoc V. Le, Alex J. Smola

ICCV 2007 Learning Graph Matching Tibério S. Caetano, Li Cheng, Quoc V. Le, Alexander J. Smola

NeurIPS 2006 Learning to Rank with Nonsmooth Cost Functions Christopher J. Burges, Robert Ragno, Quoc V. Le

JMLR 2006 Nonparametric Quantile Estimation Ichiro Takeuchi, Quoc V. Le, Timothy D. Sears, Alexander J. Smola

ICML 2006 Simpler Knowledge-Based Support Vector Machines Quoc V. Le, Alexander J. Smola, Thomas Gärtner

ECML-PKDD 2006 Transductive Gaussian Process Regression with Automatic Model Selection Quoc V. Le, Alexander J. Smola, Thomas Gärtner, Yasemin Altun

ICML 2005 Heteroscedastic Gaussian Process Regression Quoc V. Le, Alexander J. Smola, Stéphane Canu

NeurIPS 2005 Large-Scale Multiclass Transduction Thomas Gärtner, Quoc V. Le, Simon Burton, Alex J. Smola, Vishy Vishwanathan