← Authors

Quoc Le

36 papers · 2013–2024 · 7 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (11) 🌈 Renaissance Researcher (6) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (7) 🐝 Cross-Pollinator (12) πŸ—ΊοΈ Taxonomy Completionist (13) 🧭 Keyword Pioneer πŸ‘₯ Mega-Team (27) 🧬 Topic Evolution πŸ”¬ Deep Specialist (10) πŸ—ƒοΈ Keyword Collector (154) ⚑ Prolific Year (5) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ’Ž Century Club (36) πŸ”₯ Unstoppable (8) ❓ The Questioner

Conferences

ICML (16) EMNLP (9) ACL (6) ECCV (2) AAAI (1) IJCNLP (1) INTERSPEECH (1)

Top co-authors

Denny Zhou (5) Thang Luong (5) Hieu Pham (4) Jason Wei (4) Minh-Thang Luong (4) Mingxing Tan (4) Yi Tay (4) Barret Zoph (3) Chen Liang (3) Xiaodan Song (3)

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
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
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them ACL 2023
Transformer Quality in Linear Time ICML 2022
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts ICML 2022
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
AutoDropout: Learning Dropout Patterns to Regularize Deep Networks AAAI 2021
EfficientNetV2: Smaller Models and Faster Training ICML 2021
Towards Domain-Agnostic Contrastive Learning ICML 2021
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch ICML 2020
Go Wide, Then Narrow: Efficient Training of Deep Thin Networks 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
Pre-Training Transformers as Energy-Based Cloze Models EMNLP 2020
Transformer-XL: Attentive Language Models beyond a Fixed-Length Context ACL 2019
The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study ICML 2019
The Evolved Transformer ICML 2019
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks ICML 2019
AirDialogue: An Environment for Goal-Oriented Dialogue Research EMNLP 2018
Learning Longer-term Dependencies in RNNs with Auxiliary Losses ICML 2018
Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games? ICML 2018
Semi-Supervised Sequence Modeling with Cross-View Training EMNLP 2018
Understanding and Simplifying One-Shot Architecture Search ICML 2018
Efficient Neural Architecture Search via Parameters Sharing ICML 2018
Tacotron: Towards End-to-End Speech Synthesis INTERSPEECH 2017
Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision ACL 2017
Learning to Skim Text ACL 2017
Unsupervised Pretraining for Sequence to Sequence Learning EMNLP 2017
Massive Exploration of Neural Machine Translation Architectures EMNLP 2017
Addressing the Rare Word Problem in Neural Machine Translation IJCNLP 2015
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