Hyung Won Chung

According to our database1, Hyung Won Chung authored at least 27 papers between 2015 and 2023.

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Bibliography

2023
PaLM: Scaling Language Modeling with Pathways.
J. Mach. Learn. Res., 2023

Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts.
CoRR, 2023

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning.
Proceedings of the International Conference on Machine Learning, 2023

UL2: Unifying Language Learning Paradigms.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Language models are multilingual chain-of-thought reasoners.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

UniMax: Fairer and More Effective Language Sampling for Large-Scale Multilingual Pretraining.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Transcending Scaling Laws with 0.1% Extra Compute.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
Large Language Models Encode Clinical Knowledge.
CoRR, 2022

Scaling Instruction-Finetuned Language Models.
CoRR, 2022

What Language Model Architecture and Pretraining Objective Work Best for Zero-Shot Generalization?
CoRR, 2022

Scaling Up Models and Data with t5x and seqio.
CoRR, 2022

What Language Model Architecture and Pretraining Objective Works Best for Zero-Shot Generalization?
Proceedings of the International Conference on Machine Learning, 2022

Charformer: Fast Character Transformers via Gradient-based Subword Tokenization.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Scale Efficiently: Insights from Pretraining and Finetuning Transformers.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers.
CoRR, 2021

Demystifying the Better Performance of Position Encoding Variants for Transformer.
CoRR, 2021

Neural Data Augmentation via Example Extrapolation.
CoRR, 2021

Rethinking Embedding Coupling in Pre-trained Language Models.
Proceedings of the 9th International Conference on Learning Representations, 2021

Learning Compact Metrics for MT.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Do Transformer Modifications Transfer Across Implementations and Applications?
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

A Simple and Effective Positional Encoding for Transformers.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020
Finding Fast Transformers: One-Shot Neural Architecture Search by Component Composition.
CoRR, 2020

Learning to Evaluate Translation Beyond English: BLEURT Submissions to the WMT Metrics 2020 Shared Task.
Proceedings of the Fifth Conference on Machine Translation, 2020

Improving Multilingual Models with Language-Clustered Vocabularies.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2015
Entropy Generation of Desalination Powered by Variable Temperature Waste Heat.
Entropy, 2015


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