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Quoc Le

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

Achievements

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+13 more ↓ πŸ—ΊοΈ Taxonomy Completionist (13) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird
🐝 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