Youngsoo Jang

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 2 papers; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 22 citations into it
• Natural Language Processing — 17 citations into it
• Large Language Models — 6 citations into it

Whom Youngsoo Jang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Alec Radford
3. Yoshua Bengio
4. Paweł Budzianowski
5. Geoffrey E. Hinton
6. Jason Aaron Edward Weston
7. Jimmy Ba
8. Ilya Sutskever
9. Jacob Devlin
10. Alex Krizhevsky

Who trusts Youngsoo Jang overall

1. Charles Burton Snell
2. Tomasz Korbak
3. Ilya Kostrikov

Papers from Youngsoo Jang's perspective

Ordered by how strongly the researchers Youngsoo Jang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
3. Attention is All you Need (Neural Information Processing Systems)
4. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. Gradient-based learning applied to document recognition
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• End-to-End Neural Pipeline for Goal-Oriented Dialogue Systems using GPT-2 (2020) — 199 citations
• GPT-Critic: Offline Reinforcement Learning for End-to-End Task-Oriented Dialogue Systems (2022) — 46 citations