Quoc Le
35 papers · 2013–2024 · 6 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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(10)
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(6)
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Research topics
Machine Learning
(27)
Deep Learning
(23)
Optimization & Theory Β· Machine Learning
(15)
Natural Language Processing
(14)
Artificial Intelligence
(11)
Architectures
(11)
Learning Types Β· Machine Learning
(11)
Core AI
(10)
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(10)
Techniques
(8)
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(7)
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(6)
Generation
(6)
Optimization & Theory Β· Deep Learning
(6)
Core Methods
(5)
Keywords
neural architecture search
(6)
language model
(5)
recurrent neural network
(3)
few-shot learning
(3)
representation learning
(3)
large language model
(3)
neural network
(3)
language modeling
(3)
chain-of-thought prompting
(2)
reinforcement learning
(2)
unsupervised learning
(2)
transformer architecture
(2)
long-term dependency
(2)
parameter efficiency
(2)
contrastive learning
(2)
image classification
(2)
neural network optimization
(2)
self-supervised learning
(2)
machine translation
(2)
efficient computing
(2)
Papers
FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation
ACL 2024
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them
ACL 2023
Inverse Scaling Can Become U-Shaped
EMNLP 2023
Symbol tuning improves in-context learning in language models
EMNLP 2023
Transcending Scaling Laws with 0.1% Extra Compute
EMNLP 2023
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts
ICML 2022
Transformer Quality in Linear Time
ICML 2022
AutoDropout: Learning Dropout Patterns to Regularize Deep Networks
AAAI 2021
EfficientNetV2: Smaller Models and Faster Training
ICML 2021
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
ICML 2021
STraTA: Self-Training with Task Augmentation for Better Few-shot Learning
EMNLP 2021
Towards Domain-Agnostic Contrastive Learning
ICML 2021
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
ICML 2020
BigNAS: Scaling Up Neural Architecture Search with Big Single-Stage Models
ECCV 2020
Efficient Scale-Permuted Backbone with Learned Resource Distribution
ECCV 2020
Go Wide, Then Narrow: Efficient Training of Deep Thin Networks
ICML 2020
Pre-Training Transformers as Energy-Based Cloze Models
EMNLP 2020
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
ICML 2019
The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study
ICML 2019
The Evolved Transformer
ICML 2019
Transformer-XL: Attentive Language Models beyond a Fixed-Length Context
ACL 2019
AirDialogue: An Environment for Goal-Oriented Dialogue Research
EMNLP 2018
Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?
ICML 2018
Efficient Neural Architecture Search via Parameters Sharing
ICML 2018
Learning Longer-term Dependencies in RNNs with Auxiliary Losses
ICML 2018
Semi-Supervised Sequence Modeling with Cross-View Training
EMNLP 2018
Understanding and Simplifying One-Shot Architecture Search
ICML 2018
Learning to Skim Text
ACL 2017
Massive Exploration of Neural Machine Translation Architectures
EMNLP 2017
Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision
ACL 2017
Tacotron: Towards End-to-End Speech Synthesis
Interspeech 2017
Unsupervised Pretraining for Sequence to Sequence Learning
EMNLP 2017
Addressing the Rare Word Problem in Neural Machine Translation
ACL 2015
Distributed Representations of Sentences and Documents
ICML 2014
Fastfood - Computing Hilbert Space Expansions in loglinear time
ICML 2013