Barret Zoph

发表

Neural Architecture Search with Reinforcement Learning pdf

Quoc V. Le, Barret Zoph, Barret Zoph, 2016, ICLR.

AutoAugment: Learning Augmentation Policies from Data pdf

Quoc V. Le, Dandelion Mané, Barret Zoph, 2018, ArXiv.

Neural Optimizer Search with Reinforcement Learning pdf

Quoc V. Le, Barret Zoph, Vijay Vasudevan, 2017, ICML.

Efficient Neural Architecture Search via Parameter Sharing

Quoc V. Le, Melody Y. Guan, Hieu Pham, 2018, ICML.

Swish: a Self-Gated Activation Function

Quoc V. Le, Barret Zoph, Prajit Ramachandran, 2017, 1710.05941.

Randaugment: Practical automated data augmentation with a reduced search space

Quoc V. Le, Jonathon Shlens, Barret Zoph, 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Progressive Neural Architecture Search

Li Fei-Fei, Chenxi Liu, Wei Hua, 2017, ECCV.

Intriguing Properties of Adversarial Examples pdf

Quoc V. Le, Samuel S. Schoenholz, Barret Zoph, 2017, ICLR.

Understanding and Simplifying One-Shot Architecture Search

Quoc V. Le, Barret Zoph, Pieter-Jan Kindermans, 2018, ICML.

Rethinking Pre-training and Self-training pdf

Quoc V. Le, Hanxiao Liu, Yin Cui, 2020, NeurIPS.

Learning Data Augmentation Strategies for Object Detection

Quoc V. Le, Ekin D. Cubuk, Jonathon Shlens, 2019, ECCV.

Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation

Jonathon Shlens, Liang-Chieh Chen, Maxwell D. Collins, 2020, ECCV.

Multi-Source Neural Translation

Kevin Knight, Barret Zoph, Kevin Knight, 2016, NAACL.

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

Quoc V. Le, Yu Zhang, Daniel S. Park, 2019, INTERSPEECH.

Searching for Activation Functions pdf

Quoc V. Le, Barret Zoph, Prajit Ramachandran, 2018, arXiv.

Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation

Maxwell D. Collins, Raphael Gontijo Lopes, Liang-Chieh Chen, 2020, ArXiv.

Adversarial Forces of Physical Models

Ian J. Goodfellow, A. Madry, Jonas Rauber, 2020 .

Attention Augmented Convolutional Networks

Quoc V. Le, Ashish Vaswani, Jonathon Shlens, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity

Noam M. Shazeer, W. Fedus, Barret Zoph, 2021, ArXiv.

ST-MoE: Designing Stable and Transferable Sparse Expert Models

J. Dean, Noam M. Shazeer, W. Fedus, 2022, 2202.08906.

Emergent Abilities of Large Language Models

J. Dean, Oriol Vinyals, Dani Yogatama, 2022, ArXiv.

Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity

Noam M. Shazeer, W. Fedus, Barret Zoph, 2021, J. Mach. Learn. Res..

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Gerard de Melo, Andrew M. Dai, Christopher D. Manning, 2022, ArXiv.

AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty

J. Gilmer, E. D. Cubuk, Balaji Lakshminarayanan, 2019, ICLR.

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

Quoc V. Le, Andrew M. Dai, Adams Wei Yu, 2021, ICML.

A Review of Sparse Expert Models in Deep Learning

J. Dean, W. Fedus, Barret Zoph, 2022, ArXiv.

Scaling Instruction-Finetuned Language Models

Andrew M. Dai, Hyung Won Chung, J. Dean, 2022, ArXiv.

Scaling Instruction-Finetuned Language Models

Andrew M. Dai, Hyung Won Chung, J. Dean, 2022, ArXiv.

Emergent Abilities of Large Language Models

J. Dean, Oriol Vinyals, Dani Yogatama, 2022, Trans. Mach. Learn. Res..

Scaling Instruction-Finetuned Language Models

Andrew M. Dai, Hyung Won Chung, J. Dean, 2022, ArXiv.

Progressive Neural Architecture Search ( Supplementary Material )

Li Fei-Fei, Chenxi Liu, Alan Yuille, 2018 .

MAQA: A Multimodal QA Benchmark for Negation Anonymous Author(s)

Daniel M. Ziegler, Jacob Devlin, Prafulla Dhariwal, 2022 .

Faster Discovery of Neural Architectures by Searching for Paths in a Large Model

Quoc V. Le, Melody Y. Guan, Hieu Pham, 2018, ICLR.

PaLM: Scaling Language Modeling with Pathways

Andrew M. Dai, Hyung Won Chung, Thanumalayan Sankaranarayana Pillai, 2022, J. Mach. Learn. Res..

AutoAugment: Learning Augmentation Strategies From Data

Quoc V. Le, Vijay Vasudevan, Ekin D. Cubuk, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Learning Transferable Architectures for Scalable Image Recognition

Vijay Vasudevan, Jonathon Shlens, Barret Zoph, 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation

Quoc V. Le, A. Srinivas, Tsung-Yi Lin, 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning

Quoc V. Le, Hyung Won Chung, Yi Tay, 2023, ArXiv.

Revisiting ResNets: Improved Training and Scaling Strategies pdf

Ekin D. Cubuk, Jonathon Shlens, Tsung-Yi Lin, 2021, NeurIPS.

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning

Quoc V. Le, Hyung Won Chung, Yi Tay, 2023, ICML.

Transfer Learning for Low-Resource Neural Machine Translation pdf

Deniz Yuret, Kevin Knight, Jonathan May, 2016, EMNLP.

Multi-Task Self-Training for Learning General Representations pdf

Quoc V. Le, Ekin D. Cubuk, Golnaz Ghiasi, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

Randaugment: Practical automated data augmentation with a reduced search space

Quoc V. Le, Jonathon Shlens, E. D. Cubuk, 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

RandAugment: Practical data augmentation with no separate search pdf

Quoc V. Le, Ekin D. Cubuk, Jonathon Shlens, 2019, ArXiv.

Improving 3D Object Detection through Progressive Population Based Augmentation pdf

Quoc V. Le, Dragomir Anguelov, Jiquan Ngiam, 2020, ECCV.

Designing Effective Sparse Expert Models

J. Dean, Noam M. Shazeer, W. Fedus, 2022, 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW).

Searching for Efficient Multi-Scale Architectures for Dense Image Prediction

George Papandreou, Yukun Zhu, Jonathon Shlens, 2018, NeurIPS.

Simple Training Strategies and Model Scaling for Object Detection pdf

Xianzhi Du, Barret Zoph, Wei-Chih Hung, 2021, ArXiv.

A Pretrainer’s Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity

Barret Zoph, Adam Roberts, Denny Zhou, 2023, NAACL.

Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts

Hyung Won Chung, Xinyun Chen, Trevor Darrell, 2023, ArXiv.

EXPLORING NEURAL ARCHITECTURE SEARCH FOR LANGUAGE TASKS

Quoc V. Le, Adams Wei Yu, Minh-Thang Luong, 2018 .

EURAL A RCHITECTURE S EARCH WITH R EINFORCEMENT L EARNING

Quoc V. Le, Barret Zoph, 2016 .

Does Data Augmentation Benefit from Split BatchNorms pdf

Barret Zoph, Amil Merchant, Ekin Dogus Cubuk, 2020, ArXiv.

Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models

Hyung Won Chung, Xinyun Chen, K. Keutzer, 2023, 2305.14705.

GPT-4 Technical Report

Henrique Pondé de Oliveira Pinto, Daniel P. Mossing, Vitchyr H. Pong, 2023, 2303.08774.

Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation

E. D. Cubuk, Barret Zoph, Hartwig Adam, 2020, ECCV.

Scaling Instruction-Finetuned Language Models

Andrew M. Dai, Adams Wei Yu, Hyung Won Chung, 2022, ArXiv.

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Ronan Le Bras, Stuart M. Shieber, Vinay Uday Prabhu, 2022, ArXiv.

GPT-4 Technical Report

Henrique Pondé de Oliveira Pinto, OpenAI, Daniel P. Mossing, 2023, 2303.08774.

GPT-4 Technical Report

Henrique Pondé de Oliveira Pinto, Daniel P. Mossing, Vitchyr H. Pong, 2023, 2303.08774.

Zero-shot sampling of adversarial entities in biomedical question answering

Christopher A. Choquette-Choo, Daniel M. Ziegler, Alec Radford, 2024, 2402.10527.