Heteroscedastic Gaussian process regression. - Quoc V. Le; Alexander J. Smola; Stéphane Canu (ICML, 2005)

Large-Scale Multiclass Transduction. - Thomas Gärtner 001; Quoc V. Le; Simon Burton 003; Alexander J. Smola; S. V. N. Vishwanathan (NIPS, 2005)

Mapping Maintenance for Data Integration Systems. - Robert McCann; Bedoor K. AlShebli; Quoc Le 001; Hoa Nguyen; Long H. Vu; AnHai Doan (VLDB, 2005)

Transductive Gaussian Process Regression with Automatic Model Selection. - Quoc V. Le; Alexander J. Smola; Thomas Gärtner 001; Yasemin Altun (ECML, 2006)

Simpler knowledge-based support vector machines. - Quoc V. Le; Alexander J. Smola; Thomas Gärtner 001 (ICML, 2006)

Learning to Rank with Nonsmooth Cost Functions. - Christopher J. C. Burges; Robert Ragno; Quoc Viet Le (NIPS, 2006)

Nonparametric Quantile Estimation. - Ichiro Takeuchi; Quoc V. Le; Tim D. Sears; Alexander J. Smola (J. Mach. Learn. Res., 2006)

Learning Graph Matching. - Tibério S. Caetano; Li Cheng 001; Quoc V. Le; Alexander J. Smola (ICCV, 2007)

A scalable modular convex solver for regularized risk minimization. - Choon Hui Teo; Alexander J. Smola; S. V. N. Vishwanathan; Quoc V. Le (KDD, 2007)

Bundle Methods for Machine Learning. - Alexander J. Smola; S. V. N. Vishwanathan; Quoc V. Le (NIPS, 2007)

COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking . - Markus Weimer; Alexandros Karatzoglou; Quoc V. Le; Alexander J. Smola (NIPS, 2007)

Direct Optimization of Ranking Measures - Quoc V. Le; Alexander J. Smola (CoRR, 2007)

Tighter Bounds for Structured Estimation. - Olivier Chapelle; Chuong B. Do; Quoc V. Le; Alexander J. Smola; Choon Hui Teo (NIPS, 2008)

Proximal regularization for online and batch learning. - Chuong B. Do; Quoc V. Le; Chuan-Sheng Foo (ICML, 2009)

High-accuracy 3D sensing for mobile manipulation: Improving object detection and door opening. - Morgan Quigley; Siddharth Batra; Stephen Gould; Ellen Klingbeil; Quoc V. Le; Ashley Wellman; Andrew Y. Ng (ICRA, 2009)

Scalable learning for object detection with GPU hardware. - Adam Coates 002; Paul Baumstarck; Quoc V. Le; Andrew Y. Ng (IROS, 2009)

Joint calibration of multiple sensors. - Quoc V. Le; Andrew Y. Ng (IROS, 2009)

Measuring Invariances in Deep Networks. - Ian J. Goodfellow; Quoc V. Le; Andrew M. Saxe; Honglak Lee; Andrew Y. Ng (NIPS, 2009)

Estimating Labels from Label Proportions. - Novi Quadrianto; Alexander J. Smola; Tibério S. Caetano; Quoc V. Le (J. Mach. Learn. Res., 2009)

Learning Graph Matching. - Tibério S. Caetano; Julian J. McAuley; Li Cheng 001; Quoc V. Le; Alexander J. Smola (IEEE Trans. Pattern Anal. Mach. Intell., 2009)

Learning to grasp objects with multiple contact points. - Quoc V. Le; David Kamm; Arda F. Kara; Andrew Y. Ng (ICRA, 2010)

Low-cost accelerometers for robotic manipulator perception. - Morgan Quigley; Reuben D. Brewer; Sai Prashanth Soundararaj; Vijay Pradeep; Quoc V. Le; Andrew Y. Ng (IROS, 2010)

Grasping novel objects with depth segmentation. - Deepak Rao; Quoc V. Le; Thanathorn Phoka; Morgan Quigley; Attawith Sudsang; Andrew Y. Ng (IROS, 2010)

Tiled convolutional neural networks. - Quoc V. Le; Jiquan Ngiam; Zhenghao Chen; Daniel Jin hao Chia; Pang Wei Koh; Andrew Y. Ng (NIPS, 2010)

Bundle Methods for Regularized Risk Minimization. - Choon Hui Teo; S. V. N. Vishwanathan; Alexander J. Smola; Quoc V. Le (J. Mach. Learn. Res., 2010)

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 (CVPR, 2011)

On optimization methods for deep learning. - Quoc V. Le; Jiquan Ngiam; Adam Coates 002; Ahbik Lahiri; Bobby Prochnow; Andrew Y. Ng (ICML, 2011)

ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning. - Quoc V. Le; Alexandre Karpenko; Jiquan Ngiam; Andrew Y. Ng (NIPS, 2011)

Building high-level features using large scale unsupervised learning. - Quoc V. Le; Marc'Aurelio Ranzato; Rajat Monga; Matthieu Devin; Greg Corrado; Kai Chen 010; Jeffrey Dean; Andrew Y. Ng (ICML, 2012)

Recurrent Neural Networks for Noise Reduction in Robust ASR. - Andrew L. Maas; Quoc V. Le; Tyler M. O'Neil; Oriol Vinyals; Patrick Nguyen; Andrew Y. Ng (INTERSPEECH, 2012)

Learning invariant features of tumor signatures. - Quoc V. Le; Ju Han; Joe W. Gray; Paul T. Spellman; Alexander Borowsky; Bahram Parvin (ISBI, 2012)

Large Scale Distributed Deep Networks. - Jeffrey Dean; Greg Corrado; Rajat Monga; Kai Chen 010; Matthieu Devin; Quoc V. Le; Mark Z. Mao; Marc'Aurelio Ranzato; Andrew W. Senior; Paul A. Tucker; Ke Yang; Andrew Y. Ng (NIPS, 2012)

Building high-level features using large scale unsupervised learning. - Quoc V. Le (ICASSP, 2013)

On rectified linear units for speech processing. - Matthew D. Zeiler; Marc'Aurelio Ranzato; Rajat Monga; Mark Z. Mao; K. Yang; Quoc Viet Le; Patrick Nguyen; Andrew W. Senior; Vincent Vanhoucke; Jeffrey Dean; Geoffrey E. Hinton (ICASSP, 2013)

Fastfood - Computing Hilbert Space Expansions in loglinear time. - Quoc V. Le; Tamás Sarlós; Alexander J. Smola (ICML (3), 2013)

Using Web Co-occurrence Statistics for Improving Image Categorization. - Samy Bengio; Jeffrey Dean; Dumitru Erhan; Eugene Ie; Quoc V. Le; Andrew Rabinovich; Jonathon Shlens; Yoram Singer (CoRR, 2013)

Exploiting Similarities among Languages for Machine Translation. - Tomás Mikolov; Quoc V. Le; Ilya Sutskever (CoRR, 2013)

Scalable feature learning. - Quoc V. Le (2013)

Distributed Representations of Sentences and Documents. - Quoc V. Le; Tomás Mikolov (ICML, 2014)

Sequence to Sequence Learning with Neural Networks. - Ilya Sutskever; Oriol Vinyals; Quoc V. Le (NIPS, 2014)

Fastfood: Approximate Kernel Expansions in Loglinear Time. - Quoc Viet Le; Tamás Sarlós; Alexander Johannes Smola (CoRR, 2014)

Grounded Compositional Semantics for Finding and Describing Images with Sentences. - Richard Socher; Andrej Karpathy; Quoc V. Le; Christopher D. Manning; Andrew Y. Ng (Trans. Assoc. Comput. Linguistics, 2014)

Addressing the Rare Word Problem in Neural Machine Translation. - Thang Luong; Ilya Sutskever; Quoc V. Le; Oriol Vinyals; Wojciech Zaremba (ACL (1), 2015)

Semi-supervised Sequence Learning. - Andrew M. Dai; Quoc V. Le (NIPS, 2015)

Listen, Attend and Spell. - William Chan; Navdeep Jaitly; Quoc V. Le; Oriol Vinyals (CoRR, 2015)

Document Embedding with Paragraph Vectors. - Andrew M. Dai; Christopher Olah; Quoc V. Le (CoRR, 2015)

An Online Sequence-to-Sequence Model Using Partial Conditioning. - Navdeep Jaitly; Quoc V. Le; Oriol Vinyals; Ilya Sutskever; Samy Bengio (CoRR, 2015)

A Simple Way to Initialize Recurrent Networks of Rectified Linear Units. - Quoc V. Le; Navdeep Jaitly; Geoffrey E. Hinton (CoRR, 2015)

Adding Gradient Noise Improves Learning for Very Deep Networks. - Arvind Neelakantan; Luke Vilnis; Quoc V. Le; Ilya Sutskever; Lukasz Kaiser; Karol Kurach; James Martens (CoRR, 2015)

A Neural Conversational Model. - Oriol Vinyals; Quoc V. Le (CoRR, 2015)

Listen, attend and spell: A neural network for large vocabulary conversational speech recognition. - William Chan; Navdeep Jaitly; Quoc V. Le; Oriol Vinyals (ICASSP, 2016)

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

End-to-end Learning for Text and Speech. - Quoc V. Le (SSW, 2016)

Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision (Short Version). - Chen Liang; Jonathan Berant; Quoc V. Le; Kenneth D. Forbus; Ni Lao (CoRR, 2016)

Multi-task Sequence to Sequence Learning. - Minh-Thang Luong; Quoc V. Le; Ilya Sutskever; Oriol Vinyals; Lukasz Kaiser (ICLR (Poster), 2016)

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

Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation. - Yonghui Wu; Mike Schuster; Zhifeng Chen; Quoc V. Le; Mohammad Norouzi 002; Wolfgang Macherey; Maxim Krikun; Yuan Cao 007; Qin Gao; Klaus Macherey; Jeff Klingner; Apurva Shah; et al. (CoRR, 2016)

Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision. - Chen Liang; Jonathan Berant; Quoc V. Le; Kenneth D. Forbus; Ni Lao (ACL (1), 2017)

Learning to Skim Text. - Adams Wei Yu; Hongrae Lee; Quoc V. Le (ACL (1), 2017)

Unsupervised Pretraining for Sequence to Sequence Learning. - Prajit Ramachandran; Peter J. Liu; Quoc V. Le (EMNLP, 2017)

Neural Combinatorial Optimization with Reinforcement Learning. - Irwan Bello; Hieu Pham 001; Quoc V. Le; Mohammad Norouzi 002; Samy Bengio (ICLR (Workshop), 2017)

Latent Sequence Decompositions. - William Chan; Yu Zhang 033; Quoc V. Le; Navdeep Jaitly (ICLR (Poster), 2017)

HyperNetworks. - David Ha; Andrew M. Dai; Quoc V. Le (ICLR (Poster), 2017)

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

Neural Architecture Search with Reinforcement Learning. - Barret Zoph; Quoc V. Le (ICLR, 2017)

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

Device Placement Optimization with Reinforcement Learning. - Azalia Mirhoseini; Hieu Pham 001; Quoc V. Le; Benoit Steiner; Rasmus Larsen 002; Yuefeng Zhou; Naveen Kumar; Mohammad Norouzi 002; Samy Bengio; Jeff Dean (ICML, 2017)

Large-Scale Evolution of Image Classifiers. - Esteban Real; Sherry Moore; Andrew Selle; Saurabh Saxena; Yutaka I. Leon-Suematsu; Jie Tan 001; Quoc V. Le; Alexey Kurakin (ICML, 2017)

Tacotron: Towards End-to-End Speech Synthesis. - Yuxuan Wang 002; R. J. Skerry-Ryan; Daisy Stanton; Yonghui Wu; Ron J. Weiss; Navdeep Jaitly; Zongheng Yang; Ying Xiao; Zhifeng Chen; Samy Bengio; Quoc V. Le; Yannis Agiomyrgiannakis; et al. (INTERSPEECH, 2017)

Effective Domain Mixing for Neural Machine Translation. - Denny Britz; Quoc V. Le; Reid Pryzant (WMT, 2017)

Massive Exploration of Neural Machine Translation Architectures. - Denny Britz; Anna Goldie; Minh-Thang Luong; Quoc V. Le (CoRR, 2017)

Large-Scale Evolution of Image Classifiers. - Esteban Real; Sherry Moore; Andrew Selle; Saurabh Saxena; Yutaka I. Leon-Suematsu; Quoc V. Le; Alex Kurakin (CoRR, 2017)

Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model. - Yuxuan Wang 002; R. J. Skerry-Ryan; Daisy Stanton; Yonghui Wu; Ron J. Weiss; Navdeep Jaitly; Zongheng Yang; Ying Xiao; Zhifeng Chen; Samy Bengio; Quoc V. Le; Yannis Agiomyrgiannakis; et al. (CoRR, 2017)

Don't Decay the Learning Rate, Increase the Batch Size. - Samuel L. Smith; Pieter-Jan Kindermans; Quoc V. Le (CoRR, 2017)

Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation. - Melvin Johnson; Mike Schuster; Quoc V. Le; Maxim Krikun; Yonghui Wu; Zhifeng Chen; Nikhil Thorat; Fernanda B. Viégas; Martin Wattenberg; Greg Corrado; Macduff Hughes; Jeffrey Dean (Trans. Assoc. Comput. Linguistics, 2017)

Learning Transferable Architectures for Scalable Image Recognition. - Barret Zoph; Vijay Vasudevan; Jonathon Shlens; Quoc V. Le (CVPR, 2018)

Semi-Supervised Sequence Modeling with Cross-View Training. - Kevin Clark; Minh-Thang Luong; Christopher D. Manning; Quoc V. Le (EMNLP, 2018)

AirDialogue: An Environment for Goal-Oriented Dialogue Research. - Wei Wei; Quoc V. Le; Andrew M. Dai; Jia Li (EMNLP, 2018)

Evolving modular neural sequence architectures with genetic programming. - David Dohan; David R. So; Quoc V. Le (GECCO (Companion), 2018)

Intriguing Properties of Adversarial Examples. - Ekin Dogus Cubuk; Barret Zoph; Samuel S. Schoenholz; Quoc V. Le (ICLR (Workshop), 2018)

A Hierarchical Model for Device Placement. - Azalia Mirhoseini; Anna Goldie; Hieu Pham 001; Benoit Steiner; Quoc V. Le; Jeff Dean (ICLR (Poster), 2018)

Faster Discovery of Neural Architectures by Searching for Paths in a Large Model. - Hieu Pham 001; Melody Y. Guan; Barret Zoph; Quoc V. Le; Jeff Dean (ICLR (Workshop), 2018)

Searching for Activation Functions. - Prajit Ramachandran; Barret Zoph; Quoc V. Le (ICLR (Workshop), 2018)

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

A Bayesian Perspective on Generalization and Stochastic Gradient Descent. - Samuel L. Smith; Quoc V. Le (ICLR (Poster), 2018)

Learning Longer-term Dependencies in RNNs with Auxiliary Losses. - Trieu H. Trinh; Andrew M. Dai; Minh-Thang Luong; Quoc V. Le (ICLR (Workshop), 2018)

QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension. - Adams Wei Yu; David Dohan; Minh-Thang Luong; Rui Zhao; Kai Chen 010; Mohammad Norouzi 002; Quoc V. Le (ICLR (Poster), 2018)

Understanding and Simplifying One-Shot Architecture Search. - Gabriel Bender; Pieter-Jan Kindermans; Barret Zoph; Vijay Vasudevan; Quoc V. Le (ICML, 2018)

Efficient Neural Architecture Search via Parameter Sharing. - Hieu Pham 001; Melody Y. Guan; Barret Zoph; Quoc V. Le; Jeff Dean (ICML, 2018)

Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games? - Maithra Raghu; Alex Irpan; Jacob Andreas; Robert Kleinberg; Quoc V. Le; Jon M. Kleinberg (ICML, 2018)

Learning Longer-term Dependencies in RNNs with Auxiliary Losses. - Trieu H. Trinh; Andrew M. Dai; Thang Luong; Quoc V. Le (ICML, 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 002; Jonathan Berant; Quoc V. Le; Ni Lao (NeurIPS, 2018)

Neural Program Synthesis with Priority Queue Training. - Daniel A. Abolafia; Mohammad Norouzi 002; Quoc V. Le (CoRR, 2018)

Scalable and accurate deep learning for electronic health records. - Alvin Rajkomar; Eyal Oren; Kai Chen 010; Andrew M. Dai; Nissan Hajaj; Peter J. Liu; Xiaobing Liu; Mimi Sun; Patrik Sundberg; Hector Yee; Kun Zhang 043; Gavin E. Duggan; et al. (CoRR, 2018)

AutoAugment: Learning Augmentation Policies from Data. - Ekin Dogus Cubuk; Barret Zoph; Dandelion Mané; Vijay Vasudevan; Quoc V. Le (CoRR, 2018)

A Simple Method for Commonsense Reasoning. - Trieu H. Trinh; Quoc V. Le (CoRR, 2018)

Stochastic natural gradient descent draws posterior samples in function space. - Samuel L. Smith; Daniel Duckworth; Quoc V. Le; Jascha Sohl-Dickstein (CoRR, 2018)

Memory Augmented Policy Optimization for Program Synthesis with Generalization. - Chen Liang; Mohammad Norouzi 002; Jonathan Berant; Quoc V. Le; Ni Lao (CoRR, 2018)

MnasNet: Platform-Aware Neural Architecture Search for Mobile. - Mingxing Tan; Bo Chen 019; Ruoming Pang; Vijay Vasudevan; Quoc V. Le (CoRR, 2018)

Backprop Evolution. - Maximilian Alber; Irwan Bello; Barret Zoph; Pieter-Jan Kindermans; Prajit Ramachandran; Quoc V. Le (CoRR, 2018)

GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism. - Yanping Huang; Yonglong Cheng; Dehao Chen; HyoukJoong Lee; Jiquan Ngiam; Quoc V. Le; Zhifeng Chen (CoRR, 2018)

Domain Adaptive Transfer Learning with Specialist Models. - Jiquan Ngiam; Daiyi Peng; Vijay Vasudevan; Simon Kornblith; Quoc V. Le; Ruoming Pang (CoRR, 2018)

Scalable and accurate deep learning with electronic health records. - Alvin Rajkomar; Eyal Oren; Kai Chen 010; Andrew M. Dai; Nissan Hajaj; Michaela Hardt; Peter J. Liu; Xiaobing Liu; Jake Marcus; Mimi Sun; Patrik Sundberg; Hector Yee; et al. (npj Digit. Medicine, 2018)

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

BAM! Born-Again Multi-Task Networks for Natural Language Understanding. - Kevin Clark; Minh-Thang Luong; Urvashi Khandelwal; Christopher D. Manning; Quoc V. Le (ACL (1), 2019)

Transformer-XL: Attentive Language Models beyond a Fixed-Length Context. - Zihang Dai; Zhilin Yang 001; Yiming Yang; Jaime G. Carbonell; Quoc Viet Le; Ruslan Salakhutdinov (ACL (1), 2019)

MixConv: Mixed Depthwise Convolutional Kernels. - Mingxing Tan; Quoc V. Le (BMVC, 2019)

AutoAugment: Learning Augmentation Strategies From Data. - Ekin D. Cubuk; Barret Zoph; Dandelion Mané; Vijay Vasudevan; Quoc V. Le (CVPR, 2019)

NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection. - Golnaz Ghiasi; Tsung-Yi Lin; Quoc V. Le (CVPR, 2019)

Do Better ImageNet Models Transfer Better? - Simon Kornblith; Jonathon Shlens; Quoc V. Le (CVPR, 2019)

MnasNet: Platform-Aware Neural Architecture Search for Mobile. - Mingxing Tan; Bo Chen 019; Ruoming Pang; Vijay Vasudevan; Mark Sandler 002; Andrew Howard 002; Quoc V. Le (CVPR, 2019)

Attention Augmented Convolutional Networks. - Irwan Bello; Barret Zoph; Quoc Le 001; Ashish Vaswani; Jonathon Shlens (ICCV, 2019)

Searching for MobileNetV3. - Andrew Howard 002; Ruoming Pang; Hartwig Adam; Quoc V. Le; Mark Sandler 002; Bo Chen 019; Weijun Wang; Liang-Chieh Chen; Mingxing Tan; Grace Chu; Vijay Vasudevan; Yukun Zhu (ICCV, 2019)

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

The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study. - Daniel S. Park; Jascha Sohl-Dickstein; Quoc V. Le; Samuel L. Smith (ICML, 2019)

The Evolved Transformer. - David R. So; Quoc V. Le; Chen Liang (ICML, 2019)

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. - Mingxing Tan; Quoc V. Le (ICML, 2019)

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition. - Daniel S. Park; William Chan; Yu Zhang 033; Chung-Cheng Chiu; Barret Zoph; Ekin D. Cubuk; Quoc V. Le (INTERSPEECH, 2019)

Saccader: Improving Accuracy of Hard Attention Models for Vision. - Gamaleldin F. Elsayed; Simon Kornblith; 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 Xu 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)

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

XLNet: Generalized Autoregressive Pretraining for Language Understanding. - Zhilin Yang 001; Zihang Dai; Yiming Yang; Jaime G. Carbonell; Ruslan Salakhutdinov; Quoc V. Le (NeurIPS, 2019)

Mixtape: Breaking the Softmax Bottleneck Efficiently. - Zhilin Yang 001; Thang Luong; Ruslan Salakhutdinov; Quoc V. Le (NeurIPS, 2019)

Soft Conditional Computation. - Brandon Yang; Gabriel Bender; Quoc V. Le; Jiquan Ngiam (CoRR, 2019)

NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection. - Golnaz Ghiasi; Tsung-Yi Lin; Ruoming Pang; Quoc V. Le (CoRR, 2019)

Using Videos to Evaluate Image Model Robustness. - Keren Gu; Brandon Yang; Jiquan Ngiam; Quoc V. Le; Jonathon Shlens (CoRR, 2019)

Unsupervised Data Augmentation. - Qizhe Xie; Zihang Dai; Eduard H. Hovy; Minh-Thang Luong; Quoc V. Le (CoRR, 2019)

Selfie: Self-supervised Pretraining for Image Embedding. - Trieu H. Trinh; Minh-Thang Luong; Quoc V. Le (CoRR, 2019)

Neural Input Search for Large Scale Recommendation Models. - Manas R. Joglekar; Cong Li; Jay K. Adams; Pranav Khaitan; Quoc V. Le (CoRR, 2019)

RandAugment: Practical data augmentation with no separate search. - Ekin D. Cubuk; Barret Zoph; Jonathon Shlens; Quoc V. Le (CoRR, 2019)

Natural Questions: a Benchmark for Question Answering Research. - Tom Kwiatkowski; Jennimaria Palomaki; Olivia Redfield; Michael Collins 001; Ankur P. Parikh; Chris Alberti; Danielle Epstein; Illia Polosukhin; Jacob Devlin; Kenton Lee; Kristina Toutanova; Llion Jones; et al. (Trans. Assoc. Comput. Linguistics, 2019)

Can Weight Sharing Outperform Random Architecture Search? An Investigation With TuNAS. - Gabriel Bender; Hanxiao Liu; Bo Chen 019; Grace Chu; Shuyang Cheng; Pieter-Jan Kindermans; Quoc V. Le (CVPR, 2020)

MnasFPN: Learning Latency-Aware Pyramid Architecture for Object Detection on Mobile Devices. - Bo Chen 019; Golnaz Ghiasi; Hanxiao Liu; Tsung-Yi Lin; Dmitry Kalenichenko; Hartwig Adam; Quoc V. Le (CVPR, 2020)

SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization. - Xianzhi Du; Tsung-Yi Lin; Pengchong Jin; Golnaz Ghiasi; Mingxing Tan; Yin Cui; Quoc V. Le; Xiaodan Song (CVPR, 2020)

EfficientDet: Scalable and Efficient Object Detection. - Mingxing Tan; Ruoming Pang; Quoc V. Le (CVPR, 2020)

Self-Training With Noisy Student Improves ImageNet Classification. - Qizhe Xie; Minh-Thang Luong; Eduard H. Hovy; Quoc V. Le (CVPR, 2020)

Adversarial Examples Improve Image Recognition. - Cihang Xie; Mingxing Tan; Boqing Gong; Jiang Wang 001; Alan L. Yuille; Quoc V. Le (CVPR, 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; et al. (ECCV (21), 2020)

Efficient Scale-Permuted Backbone with Learned Resource Distribution. - Xianzhi Du; Tsung-Yi Lin; Pengchong Jin; Yin Cui; Mingxing Tan; Quoc V. Le; Xiaodan Song (ECCV (23), 2020)

BigNAS: Scaling up Neural Architecture Search with Big Single-Stage Models. - Jiahui Yu; Pengchong Jin; Hanxiao Liu; Gabriel Bender; Pieter-Jan Kindermans; Mingxing Tan; Thomas S. Huang; Xiaodan Song; Ruoming Pang; Quoc Le 001 (ECCV (7), 2020)

Learning Data Augmentation Strategies for Object Detection. - Barret Zoph; Ekin D. Cubuk; Golnaz Ghiasi; Tsung-Yi Lin; Jonathon Shlens; Quoc V. Le (ECCV (27), 2020)

Pre-Training Transformers as Energy-Based Cloze Models. - Kevin Clark; Minh-Thang Luong; Quoc V. Le; Christopher D. Manning (EMNLP (1), 2020)

Specaugment on Large Scale Datasets. - Daniel S. Park; Yu Zhang 033; Chung-Cheng Chiu; Youzheng Chen; Bo Li 028; William Chan; Quoc V. Le; Yonghui Wu (ICASSP, 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 (ICLR, 2020)

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators. - Kevin Clark; Minh-Thang Luong; Quoc V. Le; Christopher D. Manning (ICLR, 2020)

AutoML-Zero: Evolving Machine Learning Algorithms From Scratch. - Esteban Real; Chen Liang; David R. So; Quoc V. Le (ICML, 2020)

Go Wide, Then Narrow: Efficient Training of Deep Thin Networks. - Denny Zhou; Mao Ye 006; Chen Chen; Tianjian Meng; Mingxing Tan; Xiaodan Song; Quoc V. Le; Qiang Liu 001; Dale Schuurmans (ICML, 2020)

Improved Noisy Student Training for Automatic Speech Recognition. - Daniel S. Park; Yu Zhang 033; Ye Jia; Wei Han 002; Chung-Cheng Chiu; Bo Li 028; Yonghui Wu; Quoc V. Le (INTERSPEECH, 2020)

Neural Input Search for Large Scale Recommendation Models. - Manas R. Joglekar; Cong Li; Mei Chen; Taibai Xu; Xiaoming Wang; Jay K. Adams; Pranav Khaitan; Jiahui Liu; Quoc V. Le (KDD, 2020)

RandAugment: Practical Automated Data Augmentation with a Reduced Search Space. - Ekin Dogus Cubuk; Barret Zoph; Jonathon Shlens; Quoc Le 001 (NeurIPS, 2020)

Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing. - Zihang Dai; Guokun Lai; Yiming Yang; Quoc Le 001 (NeurIPS, 2020)

Evolving Normalization-Activation Layers. - Hanxiao Liu; Andy Brock; Karen Simonyan; Quoc Le 001 (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 Le 001 (NeurIPS, 2020)

Unsupervised Data Augmentation for Consistency Training. - Qizhe Xie; Zihang Dai; Eduard H. Hovy; Thang Luong; Quoc Le 001 (NeurIPS, 2020)

Rethinking Pre-training and Self-training. - Barret Zoph; Golnaz Ghiasi; Tsung-Yi Lin; Yin Cui; Hanxiao Liu; Ekin Dogus Cubuk; Quoc Le 001 (NeurIPS, 2020)

Towards a Human-like Open-Domain Chatbot. - Daniel Adiwardana; Minh-Thang Luong; David R. So; Jamie Hall; Noah Fiedel; Romal Thoppilan; Zi Yang; Apoorv Kulshreshtha; Gaurav Nemade; Yifeng Lu; Quoc V. Le (CoRR, 2020)

Chip Placement with Deep Reinforcement Learning. - Azalia Mirhoseini; Anna Goldie; Mustafa Yazgan; Joe W. J. Jiang; Ebrahim M. Songhori; Shen Wang; Young-Joon Lee; Eric Johnson; Omkar Pathak; Sungmin Bae; Azade Nazi; Jiwoo Pak; et al. (CoRR, 2020)

AutoHAS: Differentiable Hyper-parameter and Architecture Search. - Xuanyi Dong; Mingxing Tan; Adams Wei Yu; Daiyi Peng; Bogdan Gabrys; Quoc V. Le (CoRR, 2020)

Smooth Adversarial Training. - Cihang Xie; Mingxing Tan; Boqing Gong; Alan L. Yuille; Quoc V. Le (CoRR, 2020)

Pushing the Limits of Semi-Supervised Learning for Automatic Speech Recognition. - Yu Zhang 033; James Qin; Daniel S. Park; Wei Han 002; Chung-Cheng Chiu; Ruoming Pang; Quoc V. Le; Yonghui Wu (CoRR, 2020)

Towards Domain-Agnostic Contrastive Learning. - Vikas Verma; Minh-Thang Luong; Kenji Kawaguchi; Hieu Pham 001; Quoc V. Le (CoRR, 2020)

AutoDropout: Learning Dropout Patterns to Regularize Deep Networks. - Hieu Pham 001; Quoc V. Le (AAAI, 2021)

Searching for Fast Model Families on Datacenter Accelerators. - Sheng Li 007; 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 (CVPR, 2021)

Meta Pseudo Labels. - Hieu Pham 001; Zihang Dai; Qizhe Xie; Quoc V. Le (CVPR, 2021)

STraTA: Self-Training with Task Augmentation for Better Few-shot Learning. - Tu Vu; Minh-Thang Luong; Quoc V. Le; Grady Simon; Mohit Iyyer (EMNLP (1), 2021)

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

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

Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision. - Chao Jia; Yinfei Yang; Ye Xia 006; Yi-Ting Chen; Zarana Parekh; Hieu Pham 001; Quoc V. Le; Yun-Hsuan Sung; Zhen Li 028; Tom Duerig (ICML, 2021)

EfficientNetV2: Smaller Models and Faster Training. - Mingxing Tan; Quoc V. Le (ICML, 2021)

Towards Domain-Agnostic Contrastive Learning. - Vikas Verma; Thang Luong; Kenji Kawaguchi; Hieu Pham 001; Quoc V. Le (ICML, 2021)

Training EfficientNets at Supercomputer Scale: 83% ImageNet Top-1 Accuracy in One Hour. - Arissa Wongpanich; Hieu Pham 001; James Demmel; Mingxing Tan; Quoc V. Le; Yang You 001; Sameer Kumar (IPDPS Workshops, 2021)

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

Pay Attention to MLPs. - Hanxiao Liu; Zihang Dai; David R. So; Quoc V. Le (NeurIPS, 2021)

Searching for Efficient Transformers for Language Modeling. - David R. So; Wojciech Manke; Hanxiao Liu; Zihang Dai; Noam Shazeer; Quoc V. Le (NeurIPS, 2021)

SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network. - William Chan; Daniel S. Park; Chris A. Lee; Yu Zhang 033; Quoc V. Le; Mohammad Norouzi 002 (CoRR, 2021)

Carbon Emissions and Large Neural Network Training. - David A. Patterson 001; Joseph Gonzalez 001; Quoc V. Le; Chen Liang; Lluis-Miquel Munguia; Daniel Rothchild; David R. So; Maud Texier; Jeff Dean (CoRR, 2021)

A Full-stack Accelerator Search Technique for Vision Applications. - Dan Zhang 004; Safeen Huda; Ebrahim M. Songhori; Quoc V. Le; Anna Goldie; Azalia Mirhoseini (CoRR, 2021)

Program Synthesis with Large Language Models. - Jacob Austin; Augustus Odena; Maxwell I. Nye; Maarten Bosma; Henryk Michalewski; David Dohan; Ellen Jiang; Carrie J. Cai; Michael Terry; Quoc V. Le; Charles Sutton (CoRR, 2021)

Primer: Searching for Efficient Transformers for Language Modeling. - David R. So; Wojciech Manke; Hanxiao Liu; Zihang Dai; Noam Shazeer; Quoc V. Le (CoRR, 2021)

Combined Scaling for Zero-shot Transfer Learning. - Hieu Pham 001; Zihang Dai; Golnaz Ghiasi; Hanxiao Liu; Adams Wei Yu; Minh-Thang Luong; Mingxing Tan; Quoc V. Le (CoRR, 2021)

A graph placement methodology for fast chip design. - 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; et al. (Nat., 2021)

A full-stack search technique for domain optimized deep learning accelerators. - Dan Zhang 004; Safeen Huda; Ebrahim M. Songhori; Kartik Prabhu; Quoc V. Le; Anna Goldie; Azalia Mirhoseini (ASPLOS, 2022)

DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection. - Yingwei Li 002; 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 (CVPR, 2022)

Finetuned Language Models are Zero-Shot Learners. - Jason Wei; Maarten Bosma; Vincent Y. Zhao; Kelvin Guu; Adams Wei Yu; Brian Lester; Nan Du 002; Andrew M. Dai; Quoc V. Le (ICLR, 2022)

GLaM: Efficient Scaling of Language Models with Mixture-of-Experts. - Nan Du 002; Yanping Huang; Andrew M. Dai; Simon Tong; Dmitry Lepikhin; Yuanzhong Xu; Maxim Krikun; Yanqi Zhou; Adams Wei Yu; Orhan Firat; Barret Zoph; Liam Fedus; et al. (ICML, 2022)

Transformer Quality in Linear Time. - Weizhe Hua; Zihang Dai; Hanxiao Liu; Quoc V. Le (ICML, 2022)

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. - Jason Wei; Xuezhi Wang 002; Dale Schuurmans; Maarten Bosma; Brian Ichter; Fei Xia 002; Ed H. Chi; Quoc V. Le; Denny Zhou (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 (NeurIPS, 2022)

Mixture-of-Experts with Expert Choice Routing. - Yanqi Zhou; Tao Lei; Hanxiao Liu; Nan Du 002; Yanping Huang; Vincent Y. Zhao; Andrew M. Dai; Zhifeng Chen; Quoc V. Le; James Laudon (NeurIPS, 2022)

G-Augment: Searching for the Meta-Structure of Data Augmentation Policies for ASR. - Gary Wang; Ekin D. Cubuk; Andrew Rosenberg; Shuyang Cheng; Ron J. Weiss; Bhuvana Ramabhadran; Pedro J. Moreno 001; Quoc V. Le; Daniel S. Park (SLT, 2022)

The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink. - David A. Patterson 001; Joseph Gonzalez 001; Urs Hölzle; Quoc V. Le; Chen Liang; Lluis-Miquel Munguia; Daniel Rothchild; David R. So; Maud Texier; Jeff Dean (Computer, 2022)

LaMDA: Language Models for Dialog Applications. - Romal Thoppilan; Daniel De Freitas; Jamie Hall; Noam Shazeer; Apoorv Kulshreshtha; Heng-Tze Cheng; Alicia Jin; Taylor Bos; Leslie Baker; Yu Du; YaGuang Li; Hongrae Lee; et al. (CoRR, 2022)

Chain of Thought Prompting Elicits Reasoning in Large Language Models. - Jason Wei; Xuezhi Wang 002; Dale Schuurmans; Maarten Bosma; Ed H. Chi; Quoc Le 001; Denny Zhou (CoRR, 2022)

DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection. - Yingwei Li 002; 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; et al. (CoRR, 2022)

Self-Consistency Improves Chain of Thought Reasoning in Language Models. - Xuezhi Wang 002; Jason Wei; Dale Schuurmans; Quoc V. Le; Ed H. Chi; Denny Zhou (CoRR, 2022)

Revisiting Multi-Scale Feature Fusion for Semantic Segmentation. - Tianjian Meng; Golnaz Ghiasi; Reza Mahjourian; Quoc V. Le; Mingxing Tan (CoRR, 2022)

Resource-Constrained Neural Architecture Search on Tabular Datasets. - Chengrun Yang; Gabriel Bender; Hanxiao Liu; Pieter-Jan Kindermans; Madeleine Udell; Yifeng Lu; Quoc V. Le; Da Huang (CoRR, 2022)

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. - Denny Zhou; Nathanael Schärli; Le Hou; Jason Wei; Nathan Scales; Xuezhi Wang 002; Dale Schuurmans; Olivier Bousquet; Quoc Le 001; Ed H. Chi (CoRR, 2022)

Rationale-Augmented Ensembles in Language Models. - Xuezhi Wang 002; Jason Wei; Dale Schuurmans; Quoc V. Le; Ed H. Chi; Denny Zhou (CoRR, 2022)

Scaling Instruction-Finetuned Language Models. - Hyung Won Chung; Le Hou; Shayne Longpre; Barret Zoph; Yi Tay; William Fedus; Eric Li; Xuezhi Wang 002; Mostafa Dehghani 001; Siddhartha Brahma; Albert Webson; Shixiang Shane Gu; et al. (CoRR, 2022)

Inverse scaling can become U-shaped. - Jason Wei; Yi Tay; Quoc V. Le (CoRR, 2022)

BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition. - Yu Zhang 033; Daniel S. Park; Wei Han 002; James Qin; Anmol Gulati; Joel Shor; Aren Jansen; Yuanzhong Xu; Yanping Huang; Shibo Wang; Zongwei Zhou; Bo Li 028; et al. (IEEE J. Sel. Top. Signal Process., 2022)

Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them. - 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 (ACL (Findings), 2023)

Hyperscale Hardware Optimized Neural Architecture Search. - Sheng Li 007; Garrett Andersen; Tao Chen 003; Liqun Cheng; Julian Grady; Da Huang; Quoc V. Le; Andrew Li; Xin Li 082; Yang Li 005; Chen Liang; Yifeng Lu; et al. (ASPLOS (3), 2023)

Transcending Scaling Laws with 0.1% Extra Compute. - Yi Tay; Jason Wei; Hyung Won Chung; Vinh Q. Tran 002; David R. So; Siamak Shakeri; Xavier Garcia; Huaixiu Steven Zheng; Jinfeng Rao; Aakanksha Chowdhery; Denny Zhou; Donald Metzler; et al. (EMNLP, 2023)

Symbol tuning improves in-context learning in language models. - Jerry W. Wei; Le Hou; Andrew K. Lampinen; Xiangning Chen; Da Huang; Yi Tay; Xinyun Chen; Yifeng Lu; Denny Zhou; Tengyu Ma 001; Quoc V. Le (EMNLP, 2023)

Inverse Scaling Can Become U-Shaped. - Jason Wei; Najoung Kim; Yi Tay; Quoc V. Le (EMNLP, 2023)

Self-Consistency Improves Chain of Thought Reasoning in Language Models. - Xuezhi Wang 002; Jason Wei; Dale Schuurmans; Quoc V. Le; Ed H. Chi; Sharan Narang; Aakanksha Chowdhery; Denny Zhou (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 002; Dale Schuurmans; Claire Cui; Olivier Bousquet; Quoc V. Le; Ed H. Chi (ICLR, 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 (ICML, 2023)

Brainformers: Trading Simplicity for Efficiency. - Yanqi Zhou; Nan Du 002; Yanping Huang; Daiyi Peng; Chang Lan; Da Huang; Siamak Shakeri; David R. So; Andrew M. Dai; Yifeng Lu; Zhifeng Chen; Quoc V. Le; et al. (ICML, 2023)

Symbolic Discovery of Optimization Algorithms. - Xiangning Chen; Chen Liang; Da Huang; Esteban Real; Kaiyuan Wang; Hieu Pham 001; Xuanyi Dong; Thang Luong; Cho-Jui Hsieh; Yifeng Lu; Quoc V. Le (NeurIPS, 2023)

DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining. - Sang Michael Xie; Hieu Pham 001; Xuanyi Dong; Nan Du 002; Hanxiao Liu; Yifeng Lu; Percy Liang; Quoc V. Le; Tengyu Ma 001; Adams Wei Yu (NeurIPS, 2023)

PyGlove: Efficiently Exchanging ML Ideas as Code. - Daiyi Peng; Xuanyi Dong; Esteban Real; Yifeng Lu; Quoc V. Le (CoRR, 2023)

Noise2Music: Text-conditioned Music Generation with Diffusion Models. - 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; et al. (CoRR, 2023)

Unified Functional Hashing in Automatic Machine Learning. - Ryan Gillard; Stephen Jonany; Yingjie Miao; Michael Munn; Connal de Souza; Jonathan Dungay; Chen Liang; David R. So; Quoc V. Le; Esteban Real (CoRR, 2023)

Symbolic Discovery of Optimization Algorithms. - Xiangning Chen; Chen Liang; Da Huang; Esteban Real; Kaiyuan Wang; Yao Liu; Hieu Pham 001; Xuanyi Dong; Thang Luong; Cho-Jui Hsieh; Yifeng Lu; Quoc V. Le (CoRR, 2023)

Simple synthetic data reduces sycophancy in large language models. - Jerry W. Wei; Da Huang; Yifeng Lu; Denny Zhou; Quoc V. Le (CoRR, 2023)

AutoNumerics-Zero: Automated Discovery of State-of-the-Art Mathematical Functions. - Esteban Real; Yao Chen; Mirko Rossini; Connal de Souza; Manav Garg; Akhil Verghese; Moritz Firsching; Quoc V. Le; Ekin Dogus Cubuk; David H. Park (CoRR, 2023)

Combined scaling for zero-shot transfer learning. - Hieu Pham 001; 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 (Neurocomputing, 2023)

FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation. - Tu Vu; Mohit Iyyer; Xuezhi Wang 002; Noah Constant; Jerry W. Wei; Jason Wei; Chris Tar; Yun-Hsuan Sung; Denny Zhou; Quoc V. Le; Thang Luong (ACL (Findings), 2024)

FLIQS: One-Shot Mixed-Precision Floating-Point and Integer Quantization Search. - Jordan Dotzel; Gang Wu; Andrew Li; Muhammad Umar 002; Yun Ni; Mohamed S. Abdelfattah; Zhiru Zhang; Liqun Cheng; Martin G. Dixon; Norman P. Jouppi; Quoc V. Le; Sheng Li 007 (AutoML, 2024)

Beyond ChatBots: ExploreLLM for Structured Thoughts and Personalized Model Responses. - Xiao Ma 010; Swaroop Mishra; Ariel Liu; Sophie Ying Su; Jilin Chen; Chinmay Kulkarni 001; Heng-Tze Cheng; Quoc V. Le; Ed H. Chi (CHI Extended Abstracts, 2024)

HaloQuest: A Visual Hallucination Dataset for Advancing Multimodal Reasoning. - Zhecan Wang; Garrett Bingham; Adams Wei Yu; Quoc V. Le; Thang Luong; Golnaz Ghiasi (ECCV (77), 2024)

Large Language Models as Optimizers. - Chengrun Yang; Xuezhi Wang 002; Yifeng Lu; Hanxiao Liu; Quoc V. Le; Denny Zhou; Xinyun Chen (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 (ICLR, 2024)

Long-form factuality in large language models. - Jerry Wei; Chengrun Yang; Xinying Song; Yifeng Lu; Nathan Hu; Jie Huang 009; 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 001; Xinyun Chen; Heng-Tze Cheng; Quoc V. Le; Ed H. Chi; Denny Zhou; Swaroop Mishra; Huaixiu Steven Zheng (NeurIPS, 2024)

Long-form factuality in large language models. - Jerry Wei; Chengrun Yang; Xinying Song; Yifeng Lu; Nathan Hu; Dustin Tran; Daiyi Peng; Ruibo Liu; Da Huang; Cosmo Du; Quoc V. Le (CoRR, 2024)

NATURAL PLAN: Benchmarking LLMs on Natural Language Planning. - 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 (CoRR, 2024)

HaloQuest: A Visual Hallucination Dataset for Advancing Multimodal Reasoning. - Zhecan Wang; Garrett Bingham; Adams Yu; Quoc V. Le; Thang Luong; Golnaz Ghiasi (CoRR, 2024)

Large Language Monkeys: Scaling Inference Compute with Repeated Sampling. - Bradley C. A. Brown; Jordan Juravsky; Ryan Ehrlich; Ronald Clark; Quoc V. Le; Christopher Ré; Azalia Mirhoseini (CoRR, 2024)

Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries. - Kiran Vodrahalli; Santiago Ontanon; Nilesh Tripuraneni; Kelvin Xu; Sanil Jain; Rakesh Shivanna; Jeffrey Hui; Nishanth Dikkala; Mehran Kazemi; Bahare Fatemi; Rohan Anil; Ethan Dyer; et al. (CoRR, 2024)

EVOLvE: Evaluating and Optimizing LLMs For Exploration. - Allen Nie; Yi Su 008; Bo Chang 002; Jonathan N. Lee; Ed H. Chi; Quoc V. Le; Minmin Chen (CoRR, 2024)

Evolving Alignment via Asymmetric Self-Play. - Ziyu Ye; Rishabh Agarwal; Tianqi Liu 002; Rishabh Joshi; Sarmishta Velury; Quoc V. Le; Qijun Tan; Yuan Liu (CoRR, 2024)

Scaling Instruction-Finetuned Language Models. - Hyung Won Chung; Le Hou; Shayne Longpre; Barret Zoph; Yi Tay; William Fedus; Yunxuan Li; Xuezhi Wang 002; Mostafa Dehghani 001; Siddhartha Brahma; Albert Webson; Shixiang Shane Gu; et al. (J. Mach. Learn. Res., 2024)

Solving olympiad geometry without human demonstrations. - Trieu H. Trinh; Yuhuai Wu; Quoc V. Le; He He; Thang Luong (Nat., 2024)

BIG-Bench Extra Hard. - Mehran Kazemi; Bahare Fatemi; Hritik Bansal; John Palowitch; Chrysovalantis Anastasiou; Sanket Vaibhav Mehta; Lalit K. Jain; Virginia Aglietti; Disha Jindal; Peter Chen; Nishanth Dikkala; Gladys Tyen; et al. (ACL (1), 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 001 (CoRR, 2025)

Gold-medalist Performance in Solving Olympiad Geometry with AlphaGeometry2. - Yuri Chervonyi; Trieu H. Trinh; Miroslav Olsák; Xiaomeng Yang; Hoang Nguyen; Marcelo Menegali; Junehyuk Jung; Vikas Verma; Quoc V. Le; Thang Luong (CoRR, 2025)

BIG-Bench Extra Hard. - Mehran Kazemi; Bahare Fatemi; Hritik Bansal; John Palowitch; Chrysovalantis Anastasiou; Sanket Vaibhav Mehta; Kshitij Jain 001; Virginia Aglietti; Disha Jindal; Peter Chen; Nishanth Dikkala; Gladys Tyen; et al. (CoRR, 2025)